Dataset: 11.1K articles from the COVID-19 Open Research Dataset (PMC Open Access subset)
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Deep Learning Technology: Sebastian Arnold, Betty van Aken, Paul Grundmann, Felix A. Gers and Alexander Löser. Learning Contextualized Document Representations for Healthcare Answer Retrieval. The Web Conference 2020 (WWW'20)
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The financing, provision, and quality of healthcare systems; the availability of vaccines, antivirals, and antibiotics medicines, and appropriate compliance to treatment protocols are all important determinants of infectious disease transmission. Although the correlation between healthcare system financing and efficacy is not perfect, recent budget cuts to healthcare are an important consideration when anticipating infectious disease risk. In part related to the global economic crisis, it has been reported that many high-income governments have introduced policies to lower spending through cutting the prices of medical products and, for example, through budget restrictions and wage cuts in hospitals (54). There are many indirect and direct pathways through which budget cuts could affect disease transmission; to provide just one example, it has been estimated that 20–30% of healthcare-associated infections are preventable with intensive hygiene and control programmes2 – should investments in this area diminish, then healthcare-acquired infections could become an even more problematic issue. There are currently roughly 4.1 million healthcare-associated infections each year in the EU alone.3
A broader issue related to healthcare provision is population mobility for both healthcare professionals and patients who might increasingly seek work or healthcare in other countries – the provision of cross-border healthcare and the mitigation of cross-border health threats will necessitate collaboration across borders (55, 56) and solutions for the brain-drain of medical personnel from resource-poor countries (57). Also related to the healthcare provision and practice is the over-prescription or overuse of antibiotics. In combination with a lag in pharmaceutical innovation, rapid transmission, and poor infection control measures, this has driven resistance of organisms such as methicillin-resistant Staphylococcus aureus, or extended-spectrum beta-lactamases, and carbapenemase-producing gram-negatives such as Klebsiella pneumoniae carbapenemase (KPC) (58). Antimicrobial resistance is currently one of the major health risks facing society (59).
Food production systems remain a persistent source for human infectious diseases. Attempts are underway to estimate the global burden of food-borne disease (60), which is likely substantial. Many factors in food production affect human health. A vast range of familiar human pathogens can be acquired through the consumption of animal products and other disease drivers, such as global travel, further provoke this (61). In addition to farmed animals, the hunting and slaughtering of wild animals has led to the emergence of more exotic pathogens: SARS originated in wildlife markets and restaurants in southern China (62) and HIV and Ebola have both been linked to the hunting or slaughtering of primates and other wild animals (33, 63, 64). The density and health of livestock, meanwhile, have been linked to disease in humans (65, 66). Although inconclusive, there is some evidence to suggest that livestock production may lead to increased antibiotic resistance in human pathogens. There are certainly many pathways by which drug resistant pathogens could transmit from livestock to humans, including environmental contamination by excreted veterinary antibiotics (33, 67, 68).
Social and demographic contexts can significantly influence the transmission of infectious disease, while also creating increased vulnerabilities for some population subgroups. The elderly are at greater risk of many infectious diseases, and the ageing trend in many high-income countries could increase the challenges related to nosocomial (hospital-acquired) and nursing-home acquired infections. An additional challenge related to population ageing is that the share of employed workers in a country decreases. The combination of more people to care for and fewer tax-related revenues may challenge publicly financed public health and disease control programmes (7).
When persons from regions with high endemicity of a given disease move to ones with lower endemicity, new challenges for public health are created. In addition migrant communities can be highly vulnerable to certain infectious diseases. In the EU, for example, approximately 37% of HIV cases reported in 2011 were among people born abroad, and the equivalent number of cases for tuberculosis was 25% (40). Similarly, migrants suffer from a higher burden of chronic hepatitis B infections (41).
It is widely established that socially and economically disadvantaged groups suffer disproportionally from disease (42). This is applicable to infectious disease burdens in both high- and low-income settings (43, 44). Income inequalities are generally widening globally, and this appears to be have been exacerbated in many countries due to the global economic crisis (45). Rising unemployment and the prospect of public health budget cuts can increase the risk of infectious disease transmission (44, 46), with a prominent example being an outbreak of HIV among people who inject drugs (PWID) in Greece (see ‘Measles among Roma in Bulgaria and HIV among PWID in Greece: the impact of socioeconomic contexts’ section) (47, 48). In a similar fashion, it has been speculated that tuberculosis rates could rise in some countries in Central and Eastern Europe (49).
Social trends and behaviours can also play a significant role in infectious disease transmission. The most notable example would be vaccine hesitancy, the phenomenon through which vaccination coverage rates remain suboptimal due to the varying and complicated reasons that individuals may have for not getting vaccinated (50, 51). In some cases, this might be related to misconceptions about the safety or efficacy of vaccines (50, 52), whereas in others this may be related to religious or cultural beliefs (53).
Hepatitis B is found in virtually every region of the globe. Of the more than 2 billion people who are or have been infected, 350 to 400 million are carriers of the chronic disease; the remainder undergo spontaneous recovery and production of protective antibodies. Nearly 100% of infected infants (that is, those born to HBV-infected mothers) become chronically infected. The risk of developing a chronic infection decreases with age.
At least 30% of those with chronic HBV infection experience significant morbidity or mortality, including cirrhosis and hepatocellular carcinoma. Most people do not know they are infected until they present with symptoms of advanced liver disease, which means that infected individuals can spread the infection unknowingly, sometimes for many years. Although oral antiviral therapies are effective at stopping HBV replication, they do not cure the disease. Therefore, therapy is usually lifelong. Treatment is also complicated by the development of drug resistance and side effects. A vaccine against HBV is safe and effective in 90 to 95% of people; however, the individuals who are most at risk of becoming infected are often those with limited access to the vaccine, such as marginalized populations or people living in resource-limited countries.
There is substantial evidence that an individual's likelihood of recovering from an acute HBV infection or developing severe sequelae from infection is influenced, in part, by genes [39–45]. Candidate gene and genome-wide association studies have identified variants associated with HBV-related disease progression or hepatocellular carcinoma in various populations [46–52]. Treatment response to interferon (IFN)-α has been associated in some, but not all, studies with IFNλ3 polymorphisms. Finally, specific gene variants (HLA and non-HLA alleles) have been associated with vaccine response and non-response [54–57].
Guinea pigs and golden hamsters were found to be relatively resistant to MPXV (West African clade Copenhagen strain) infection by multiple routes. Guinea pigs were challenged via an intracardial, intranasal (IN), oral or foot pad (FP) inoculation with no observable symptoms of disease except for edema at the FP inoculation site. Golden hamsters were also resistant to MPXV infection via several routes of infection with no observable signs of disease, even with large dosages of virus (1.5–5.9 × 107).
Rabbits have also been considered as a possible animal model for the study of MPXV [2–3]; susceptibility depended greatly on the method of inoculation and the age of the animals. In adult rabbits challenged with MPXV (West African clade Copenhagen strain) via an oral inoculation, no signs of disease were seen. However, if virus was delivered by intravenous route, acute illness was observed with generalized rash. Young rabbits (10 days old) inoculated via IN or oral route developed severe illness; two day old rabbits were highly susceptible to infection by intracutaneous inoculation or skin scarification. The intracutaneous route led to the development of discrete white translucent lesions. Another study found that intracerebral inoculation was 100% fatal and that intratesticular or intracorneal inoculation with MPXV was also pathogenic in rabbits.
Several rat species including white rats, cotton rats and multimammate rats have been challenged with MPXV. Adult white rats inoculated with 101 to 103 plaque forming units (pfu) of West African MPXV were not susceptible to infection with intravenous, IN, or cutaneous routes of infection. However, newborn white rats (1–3 days old) developed adynamia leading to death in 5–8 days when challenged with MPXV intranasally. Cotton rats and multimammate rats were both found to be highly susceptible to MPXV infection. When cotton rats were challenged with 105 pfu via an intravenous route of infection, 100% mortality was seen 4–5 days post infection (p.i.). The infection was characterized by difficulty breathing, cough, sneezing, cyanosis, rhinitis, purulent conjunctivitis, and progressive emaciation. An IN MPXV challenge in cotton rats caused 50% mortality with a clinical picture such as that seen with the intravenous route. Multimammate rats were highly sensitive to both IN and intraperitoneal (IP) inoculation.
Marennikova et al. challenged adult common squirrels (Sciurus vulgaris) with 106 pfu of MPXV Z-249 (Congo Basin clade) via IN, oral or scarification routes of infection. Disease progression occurred earlier in animals infected IN or orally than those animals infected via a scarification route. Skin lesions did not develop on any animals; symptoms of disease included fever, inactivity, inappetence, rhinitis, cough and difficulty breathing. Infection was 100% lethal by day 7 or 8 p.i. regardless of inoculation route. Shelukhina et al. challenged six African squirrel species (including members of the genera Funisciurus, Protexerus and Heliosciurus) with Congo Basin MPXV via an IN infection (105 or 106 pfu/0.1 mL). All squirrel species were highly susceptible to Congo Basin MPXV challenge and developed an acute, generalized infection that was 100% lethal. However, some varying degree of susceptibility in the different squirrel species was seen with lesser dosages of virus. Cutaneous inoculation of squirrels resulted in a thick, red papule at the inoculation site. Skin lesions (restricted to non-fur-bearing areas of the skin or at the borders of the skin and mucous membranes of the nose and lip) occurred in only a few squirrels that had been infected by the oral or IN route with small (nonlethal) doses of virus. Most often the rash appeared in the later stages of disease (16–25 days p.i.). Transmission studies were also conducted with squirrels and authors found that infected animals were able to transmit the disease to naïve animals via airborne and direct contact.
Ground squirrels (Spermophilus tridecemlineatus) are very susceptible to MPXV infection. Tesh et al. challenged adult ground squirrels with the West African MPXV clade either IP or IN with 105.1 pfu. In both groups, symptoms of disease included anorexia and lethargy within 4–5 days of infection, with no other observable symptoms. Weight loss was not measured for these animals. Animals in the IP group died within 6–7 days p.i.; those IN challenged all died within 8–9 days. A follow-up study compared the pathogenesis of the two MPVX clades in the ground squirrel model. Inoculation of 100 pfu by a subcutaneous route of infection was 100% lethal for both MPXV clades. However, the authors noted that the onset of severe respiratory distress was more rapid and uniform for the Congo Basin MPXV challenged animals. Additionally, animals challenged with the Congo Basin MPXV began to die earlier than West African challenged animals. However, LD50 values were similar for the two strains using the ground squirrel MPXV model (0.35 pfu for Congo Basin and 0.46 pfu for West African MPXV).
Prairie dogs have also been looked at as a possible MPXV animal model. Xiao et al. challenged prairie dogs with 105.1 pfu of West African MPXV via an IP or IN route of infection and observed 100% and 60% mortality, respectively. Hutson et al. challenged prairie dogs with either the Congo Basin or West African MPXV (104.5 pfu) via an IN or scarification route of infection. Animals were asymptomatic until days 9–12 when a generalized rash was observed on challenged animals. Signs of disease included lethargy, inappetence, nasal discharge, respiratory distress, and diarrhea; morbidity was noticeably more for the Congo Basin MPXV challenged animals as was mortality. A follow-up study found the LD50 for the prairie dog MPXV model is approximately a hundred-times lower for the Congo Basin clade compared to the West African clade (5.9 × 103 and 1.29 × 105, respectively), utilizing an IN route of infection. Weight loss occurred in 2/4 West African MPXV challenged dosage groups and 3/4 Congo Basin MPXV challenged dosage groups; for both viral strains the highest percent weight loss calculated occurred in the highest viral inoculum group. A trend of increasing viral titers in oropharyngeal swabs with increasing viral inoculums dose was apparent for both MPXV strains, and when all mean values were combined, Congo Basin challenged animals had statistically higher levels of virus. Furthermore, the duration of MPXV DNA and viral shedding tended to occur earlier, attain higher levels, and persist longer for Congo Basin challenged animals. Symptoms were also more numerous and severe for Congo Basin MPXV infected prairie dogs.
Schultz et al. challenged African dormice, Graphiuris kelleni, with 1.4 × 104 pfu of a Congo Basin clade of MPXV via FP route and observed 92% mortality. The authors further developed the model by infecting dormice with various dosages of Congo Basin MPXV by the IN route and calculated the LD50 as 12 pfu. Animals became symptomatic at day 3 (conjunctivitis and dehydration), and animals that succumbed to disease had a mean time to death of 7.9 ± 1 to 12.3 ± 5 days (depending on dose). Morbidity for those animals that succumbed to disease included decreased activity, hunched posture, unkempt hair coat, dehydration, and conjunctivitis; lesions did not develop on any animals. Weight loss was highest with 2,000 pfu (the highest dosage given), but also was seen in animals given 200 or 20 pfu. Weight loss was not observed in the lowest dosage groups (2 and 0.2 pfu). Disease pathogenesis was described as localized inflammation, viral replication and hemorrhage in the nasal mucosa, followed by dissemination around day 3 with subsequent necrosis of liver, spleen, lung and gastrointestinal tract tissues. When the West African strain of MPXV was used to challenge dormice by an IN infection, similar days until death and mortality rates were seen as the Congo Basin MPXV challenged animals.
As is the case for many pathogens, mice have been utilized numerous times for the study of MPXV. Results have varied greatly depending on the type of mice used (i.e., wild strains or laboratory strains). In early studies white mice were challenged via intracerebral, IN, IP, FP, oral or intradermal (ID) inoculation with a West African strain of MPXV and found to be highly sensitive to most inoculation routes. Intracerebral inoculation was 100% fatal in adult white mice as was IN inoculation of suckling mice. Inoculation in eight day old mice via the FP, IP, or IN route resulted in 100% mortality; ID or oral inoculation caused 50% and 40% mortality, respectively. Oral inoculation of 12 day old white mice only caused 14% mortality; however IN inoculation in 15 day old animals led to 100% mortality. Inbred laboratory mouse strains have also been studied by several groups. Hutson et al. compared the two clades of virus (105 pfu) in immunocompetent BALB/c and C57BL/6 laboratory mouse strains via an IN or FP route of infection. Localized signs in the FP challenged animals included edema at the inoculation site, while the Congo Basin IN route of infection led to weight loss. However, symptoms were minimal and all animals survived infection. Osorio et al. compared both clades of virus by an IP inoculation in either BALB/c or severe combined immune deficient (SCID) BALB/c mice. Biophotonic imaging was used to visualize the disease progression. BALB/c mice developed rough coats, and decreased activity but cleared infection within 10 days p.i. In contrast, SCID BALB/c mice developed similar symptoms, but resulted in 100% mortality by day 9 p.i. (Congo Basin MPXV) or day 11 p.i. (West African MPXV). Stabenow et al. utilized a laboratory mouse strain lacking STAT1 (C57BL/6stat-/-), an important protein involved in Type I and Type II IFN signaling. Mice were challenged with dosages between 4.7 to 4,700 pfu via an IN route of infection. Weight loss was seen with all dosages given except for the lowest (4.7 pfu). Mortality occurred at 25–50% at the 47 pfu dose (12–21 days p.i.); 100% mortality occurred by day 9 p.i. with the highest dose given (4,700 pfu). The calculated LD50 for the Congo Basin clade in the C57BL/6stat-/- mice was 213 and 47 pfu for females and males, respectively. Americo et al. screened 38 inbred mouse strains and identified three that are highly susceptible to MPXV. Of these three strains, the CAST/EiJ was developed as a model. Signs of morbidity in moribund animals included ruffled fur, hunched posture, and lethargy; no animals developed lesions. Animals challenged with the highest dosages by an IN route (105 or 106 pfu Congo Basin MPXV) lost up to 28% of the starting body weight and 100% died between days 5–8. Animals challenged with 104 pfu all died between days 8–10. Animals challenged with 103 pfu had an even longer delay in weight loss and death and 40% of the animals recovered. No animals perished in the 102 pfu challenge group. The calculated LD50 for the Congo Basin clade in the CAST/EiJ mice given an IN challenge was 680 pfu. Animals were found to be even more sensitive with an IP Congo Basin MPXV infection and the calculated LD50 was 14 pfu. Challenging mice with 105 or 106 pfu of a West African MPXV strain resulted in rapid weight loss and 100% mortality by day 8 p.i. Lower dosages of West African MPXV resulted in less weight loss and lower amounts of death than what was observed for the Congo Basin MPXV; the calculated LD50 was 7,600 pfu, more than a log higher than for the Congo Basin clade.
The studied communities were located within 95 km (severe neurological infectious disease) and 62 km (fatal respiratory infectious disease) of a surveillance hospital. In these communities, 76 of 426 severe neurological disease cases (18%, 95% CI 14%–22%) and 234 of 1,630 fatal respiratory disease cases (14%, 95% CI 13%–16%) attended a surveillance hospital. Adjusting for distance, the case detection probability was nearly twice as high among severe neurological disease cases than among fatal respiratory disease cases (risk ratio 1.8, 95% CI 1.4–2.3; p < 0.001). At 10 km distance, an estimated 26% (95% CI 18%–33%) of severe neurological disease cases and 18% (95% CI 16%–21%) of fatal respiratory disease cases were detected by the hospital-based surveillance. The detection probability decreased with distance from the surveillance hospital, and the decline was faster for fatal respiratory disease than for severe neurological disease. A 10 km distance increase resulted in a 12% (95% CI 4%–19%; p = 0.003) relative reduction in case detection probability for severe neurological disease but a 36% (95% CI 29%–43%; p < 0.001) relative reduction for fatal respiratory disease (Fig 2C). Including more complex functional forms of distance in the log-binomial regression models did not improve model fit based on AIC (Table A and Figs. B and C in S1 Text).
The probability of detecting an outbreak of exactly three cases (if a single detected case was considered an outbreak) dropped below 50% at distances greater than 26 km for severe neurological disease and at distances greater than 7 km for fatal respiratory disease (Fig 3A). Fig 3B and 3C show the minimum number of cases required for surveillance to detect outbreaks with a probability of ≥90% if different outbreak thresholds are applied. For outbreaks defined as detection of at least one case, we found that an outbreak of fatal respiratory disease required 12 cases (95% CI 11–13) to be detected with 90% probability at 10 km from a surveillance hospital, but 30 cases (95% CI 24–39) to be detected at 30 km. In contrast, the impact of distance on the outbreak size requirement was much more limited for severe neurological disease: eight cases (95% CI 6–12) at 10 km and 11 cases (95% CI 9–14) at 30 km. For outbreaks defined as detection of at least two cases, 14 severe neurological disease cases (95% CI 11–20) and 20 fatal respiratory disease cases (95% CI 18–23) would be necessary for an outbreak to be detected at 10 km distance, and 19 severe neurological disease cases (95% CI 15–24) and 51 fatal respiratory disease cases (95% CI 41–66) at 30 km. The necessary outbreak sizes increased further when a five-case threshold was applied, so that 28 severe neurological disease cases (95% CI 21–39) and 39 fatal respiratory disease cases (95% CI 35–44) would need to occur for an outbreak to be detected at 10 km distance, and 36 (95% CI 30–46) and 97 (95% CI 79–128), respectively, cases at 30 km.
Surveillance hospital attendance among community cases varied by case characteristics, leading sometimes to biased disease statistics among surveillance cases (Table B in S1 Text). For severe neurological disease, individuals aged <5 y represented 48% of community cases but only 29% of surveillance cases (p < 0.001). Additionally, the proportion of cases in the lowest socioeconomic group was lower among surveillance cases than among community cases (43% versus 57%; p = 0.012), while the proportion of individuals aged 15–59 y was higher (43% versus 29%; p = 0.005) (Fig 4A). For fatal respiratory disease, the proportion of individuals aged ≥60 y (47% versus 62%; p < 0.001) was lower among surveillance cases than among community cases, while the proportion of individuals aged <5 y (24% versus 18%; p = 0.020), individuals aged 15–59 y (27% versus 18%; p < 0.001), and cases in the highest socioeconomic group (43% versus 37%; p = 0.022) was higher (Fig 4B). We observed a slight difference in the proportion of females for fatal respiratory disease (34% among surveillance cases versus 38% among community cases; p = 0.108), but not for severe neurological disease (39% versus 40%; p = 0.861). Results were consistent in sensitivity analyses with age as a continuous variable and socioeconomic status classified into quintiles (Figs. D and E in S1 Text).
A substantial proportion of cases (severe neurological disease 42% [95% CI 38%–47%]; fatal respiratory disease 26% [95% CI 24%–28%]) visited multiple healthcare providers during their illness. Forty-eight percent (95% CI 44%–53%) of severe neurological disease cases and 31% (95% CI 29%–34%) of fatal respiratory disease cases attended any hospital, including surveillance hospitals (Fig 5). Including other hospitals that were attended by cases in the surveillance system could have increased the overall case detection probability by 31% (absolute increase) for severe neurological disease cases and 17% for fatal respiratory disease cases. The capacity to detect outbreaks would have increased, so that outbreaks containing four severe neurological or eight fatal respiratory disease cases would have been detected with ≥90% probability for any distance in the range 0–40 km from the original surveillance hospital, compared to 13 and 47 cases, respectively, with the current system (Fig. F in S1 Text). However, since individuals who attended any hospital had similar characteristics in terms of sex, age, and socioeconomic status as those attending surveillance hospitals (Fig. G in S1 Text), this expansion would not have increased disease detection in key groups such as the lowest socioeconomic group. Only with the informal sector incorporated in the surveillance system would cases in such groups be detected.
To date, four MPXV small animal models have been used for the testing of antiviral drugs Cidofovir, CMX001 and ST246 (tecovirimat). Herein we will summarize those studies, efficacy data, and discuss the advantages, and limitations, of the animal models used.
Sbrana et al. utilized ground squirrels to test the efficacy of ST-246 against a MPXV challenge. The authors used 100 pfu of MPX-ZAI-1970 (200 × LD50) via a subcutaneous route of inoculation. Squirrels (8–9 per group) were divided into five treatment groups; drug was given either at 0 hours of infection, 24 hours, 48 hours, 72 hours or 96 hours p.i. 100 mg/kg of drug was given once a day for 14 days. Two animals in each group were sacrificed at day 7 to measure objective morbidity; the remainder of the animals were used to calculate survival rates. Animals in the placebo group, that were not given ST-246, showed signs of illness beginning on day 4 and all died between days 6–9. Signs of disease included lethargy, anorexia, nosebleeds, and terminal respiratory distress. At day 7, a sampling of placebo-treated animals exhibited significant leukocytosis, transaminitis, and coagulopathy; almost 105 pfu/mL of infectious monkeypox was found in blood; at this time, between 107 and 108 pfu /mL of infectious MPXV was observed in 10% organ homogenates of liver, spleen and lung. Animals treated on days 0, 24, 48 or 72 hours, before symptomatic disease onset, all survived infection and showed no signs of disease. At day 7, in a sampling of animals treated at hour 0, 24, 48 or 72 p.i., no virus was found in the liver, spleen, lung, or blood; although some abnormal values were apparently recorded, no clear trends in leukocytosis, transaminitis or coagulopathy were noted with delay in treatment onset. In animals initiating treatment at 96 hours p.i., concurrent with symptomatic disease onset, 67% of animals survived infection. 2/4 survivors showed signs of disease. In those animals that succumbed to infection, ST-246 prolonged the time to death; the mean time to death was day 7 for animals receiving placebo and day 13 for those receiving ST-246 in the 96 hour p.i. treatment group. The sampling of animals at day 7, initiating ST-246 at 96 hour p.i., demonstrated lower levels of viremia (∼3 log decrease) and ∼5 logs less virus in liver, spleen and lungs than that seen on the placebo treated animals at day 7. Although some evidence of transaminitis was present, leukocytosis and coagulopathy were not observed in this treatment group. Pathologic examination of tissues in general showed greater tissue necrosis in animals treated at later times p.i. This study was able to demonstrate a survival benefit in animals treated prior to, or at the onset of disease symptoms, in a disease model that has a time course attenuated with respect to what is seen in human disease.
Schultz et al. infected African dormice with a lethal challenge of Congo Basin clade virus MPXV-ZAI-79 via an IN route of infection to evaluate the efficacy of Cidofovir as post exposure prophylaxis. Four hours post intranasal infection with 75, 4 × 103, or 5 × 103 pfu of MPXV, animals were intraperitoneally administered 100 mg/kg cidofovir (the calculated LD50 for the dormouse MPXV model was 12 pfu). Aggregate data from all challenges showed animals treated with cidofovir had a mortality rate of 19% (7/36), whereas vehicle treated animals all (41/41) succumbed to disease. Treatment initiation at later times p.i. was not evaluated; effects on viral load or histopathologic changes were not reported.
As inbred mice have historically shown little disease symptomatology or pathogenesis post monkeypox infection, Stabenow et al. utilized a laboratory mouse strain lacking STAT1 (C57BL/6stat-/-), which has been found to be sensitive to a range of viruses including SARS, murine norovirus 1, respiratory viruses, dengue virus and MPXV [19,22–25]. These animals are deficient in their ability to transcribe many of the Type I and Type II receptor interferon response genes. The authors used the Congo Basin clade virus MPX-ZAI-79, evaluated disease and the protective efficacy of CMX001 and ST246. In untreated mice, 0% mortality was observed with 4.7 pfu challenge, 90% mortality with 470 pfu of virus and 100% mortality with 4,700 pfu. Over 25% total body weight loss, and mortality was observed on or prior to day 10 p.i. in untreated animals. Animals in the treatment studies were subsequently challenged with 5,000 pfu via an IN infection. Animals were then treated with 10 mg/kg of CMX001 by gastric gavage on the day of challenge followed by every other day with 2.5 mg/kg until day 14 p.i. All C57BL/6 stat-/- mice that were treated with drug survived infection, demonstrated <10% body weight loss between days 10 and 20, and developed a serologic response to monkeypox. Similarly, mice treated daily, starting at the day of virus challenge, with 100mg/kg of ST246 for 10 days also survived infection and manifest <10% body weight loss between days 10 and 20. In this system, antiviral treated animals rechallenged with monkeypox at day 38 post initial infection (at least 10 days post reinitiation of steady weight gain), manifest 20% mortality. The model—again one with a short disease course—is useful for demonstrating immediate post exposure efficacy of antiviral treatment in the absence of a functioning interferon response system. Additionally, in this animal model system, perhaps due to the immune defect, a monkeypox protective immune response was not elicited in all animals receiving antiviral treatment. This observation merits further observation in other animal model systems.
Smith et al. tested the efficacy of ST246 in a prairie dog MPXV model. MPXV challenged prairie dogs have previously been shown to have an asymptomatic period followed by symptoms of disease including lethargy, nasal discharge, inappetence, weight loss and systemic lesion development most commonly between days 9–12. In the current study, animals were inoculated via an IN challenge with the Congo Basin clade virus ROC-2003-358. This is a different strain of MPXV than that used in the previous described studies, but is also a strain belonging to the Congo Basin clade. The challenge dose was 3.8 × 105, equal to 65 × LD50 for the prairie dog model. Animals were divided into three treatment groups; prophylactic (day 0), post exposure (day 3) and therapeutic (varying day based on rash onset), and a control vehicle treated group. ST246 was formulated at 30 mg/mL and administered daily, by oral gavage, for 14 days. Animals initiating treatment at day 0 or 3 were protected from death and apparent signs of illness. Animals treated at rash onset had symptoms similar to the placebo control group; however symptoms were less severe in the treated animals. Although all animals treated at rash onset survived infection, animals lost 10–24% of body weight and did develop generalized rash (however, lesions resolved more quickly when compared to untreated prairie dogs in previous studies. Although asymptomatic, viable virus was shed sporadically from animals in the prophylaxis and post exposure groups (from two oropharyngeal samples in the day 0 prophylaxis group, and five samples from the day 3 post exposure group). More, sustained virus was detected in the oropharyngeal samplings of the animals in the therapeutic treatment group, but levels were less than the virus levels in the untreated group. 1/4 sham-treated animals survived infection. Signs of disease and viral titers were all increased in this group of animals compared to the animals treated with ST-246. This is the first small animal study where a treatment and survival benefit has been demonstrated when animals are treated at later stages of illness. Initiation of treatment at rash onset is similar to expectations of a human treatment regimen. The observation of virus shedding after treatment cessation in the prophylactically or post exposure treated animals merits further study to assess whether this reflects viral resistance or a blunted and delayed immune recognition and ultimate clearance of virus.
With all the probabilities calculated already, we can calculate the total probability of entry of the disease j from the country i to the European Union, taking into account all the routes of entry already evaluated(PIij).
To do this, we calculate the probability of occurrence of the opposite case, the probability of no introduction of the j disease by any of the routes of entry, using the following formula:
With the same type of formula, it is estimated the likelihood of entry of a disease j in the European Union.
A high, moderate and low risk of introduction of infectious diseases from different countries has been estimated based on a 75 and 90-percentile (P75 and P90) over the final results of probability of each route of entry. Therefore, the results that are over the 75-percentile and 90-percentile are classified as moderate and high risk of entry.
This work has made possible to assess the risk of entry of different infectious diseases at the same time, and through different routes of entry into a large geographical area.
The use of spread sheets for the development of probabilistic formulation has been of vital importance for the collection and analysis of data, although its validity depends on the confidence and quality of the available information. In this case, there is only complete information of five countries: Morocco, Algeria, Tunisia, Egypt, and Saudi Arabia.
It has been established a model for vectors introduction in wind flow that confirms the potential entry by this pathway of some vector-borne diseases, bluetongue and epizootic haemorrhagic disease, from Morocco, Algeria and Tunisia.
Of all the diseases analyzed in this study, Newcastle disease and avian influenza are the ones with a higher risk of entry in the European Union. The pathway with more relevance in the risk of entry of these diseases is the wild bird's migration.
The diseases with a moderate risk of entry are bluetongue, epizootic haemorrhagic disease and foot and mouth disease. These diseases have in common the possible entry through wind dispersion. In the case of vector-borne diseases it is possible by vectors dispersion in wind currents, and in the case of foot and mouth disease it is possible by virus spreading through wind currents.
Due to the absence of live dromedary movement to Europe, the more likely way of entry of the Middle East respiratory syndrome is through infected people movement, from Saudi Arabia, Kuwait, Qatar and Oman.
The contagious bovine pleuropneumonia is the only disease with no risk of introduction in the European Union, due to the absence of cattle movement from the countries affected by this disease, Chad, Niger, Mali, and Mauritania.
Acute viral infections such as influenza also have profound impacts on global health. In contrast to the yearly epidemics caused by seasonal influenza, a pandemic can occur when a new virus emerges in a naive population and is readily transmitted from person to person. The US Centers for Disease Control (CDC) estimates that the H1N1 2009 pandemic resulted in 41 to 84 million infections, 183,000 to 378,000 hospitalizations, and nearly 285,000 deaths worldwide. Although the morbidity and mortality of that pandemic were lower than feared, public health professionals continuously monitor for the emergence of more virulent strains.
As an airborne infection, influenza is transmitted easily and quickly, and its effects can be acute, although there is wide variability in response to infection. Much of the heterogeneity in the severity of seasonal influenza infections has been attributed to the degree of acquired immunity in the population affected, patient co-morbidities and the virulence of the strain. Also, influenza epidemics and pandemics are often caused by the introduction of novel viruses for which most people have limited acquired immunity. The emergence of new strains, and the lack of cross-protection by existing vaccines, does not leave much time for vaccine development. In pandemics, including the H1N1 2009 influenza pandemic, healthy young individuals with no co-morbidities have comprised a significant proportion of fatal and severe cases. These pandemics have provided an opportunity to evaluate the host innate immune response among populations without underlying background immunity.
Research has identified genetic factors associated with severity of illness due to influenza [63–65] and death from severe influenza. Genetic information about immune response to influenza could inform vaccine development and distribution, and disease treatment strategies. Several candidate gene studies suggest that variations in HLA class 1 and other genes contribute to differences in antibody response to influenza vaccines. Ongoing experience with vaccine use has provided opportunities to learn about the potential role of genetics in vaccine safety and efficacy.
Environmental factors, specifically climate conditions, are the seasonal drivers that have received the most attention. This may be because they often covary with seasonal disease incidence. Environmental drivers are abiotic conditions that influence transmission via their effects on hosts and/or parasites; classic examples are temperature and rainfall, which influence a variety of infectious diseases, but other examples include seasonal nonclimatic abiotic environmental conditions, such as water salinity, which may impact water-borne pathogens. Environmental factors can impact pathogen survival during transitions between hosts. Transitions can take place during short time windows (e.g., for droplet-transmitted infections) or long time windows (e.g., for parasites with environmental life stages). In addition to their impact on pathogens, environmental drivers can also influence host susceptibility to infection or vector population dynamics.
As for host susceptibility, environmental conditions can impact the host immune response and increase cells' susceptibility to infection or pose seasonal challenges (such as food limitations) that leave hosts vulnerable to infection or pathology, which has been proposed to influence disease progression in individuals infected with HIV. For directly transmitted infections, environmental conditions can be major drivers of cycles in incidence, with influenza and cholera transmission being notable examples (e.g., see [3, 80]). The effects of climate on flu transmission have been studied using population-level data coupled with transmission models, as well as empirical animal studies, to demonstrate the effects of temperature and humidity on transmission. Although climate conditions undoubtedly play a direct role in several directly transmitted infections, they may play a more nuanced role in vector-borne disease systems in which they modulate vector population dynamics and subsequently disease transmission. For example, in the case of African sleeping sickness (Table 1), the rainy season is hypothesized to modify tsetse fly distribution, which results in changes in human–tsetse fly contact and subsequently African sleeping sickness incidence; in this case, we can classify the seasonal driver as (1) vector seasonality alone or as (2) seasonal climate influencing vector seasonality and vector seasonality having a downstream effect on seasonal exposure. Abiotic and biotic seasonal drivers are therefore interconnected and not mutually exclusive.
We estimated the disease-specific case detection probability as the proportion of cases who reportedly sought care at a surveillance hospital among all cases identified during community surveys (number of surveillance cases/number of community cases) and computed 95% confidence intervals (95% CIs) based on the Clopper-Pearson exact method. We quantified case detection probabilities by distance from a surveillance hospital using log-binomial regression analysis separately for severe neurological and fatal respiratory disease cases. We further investigated more complex functional forms of distance in log-binomial regression models. We fitted models with polynomial terms up to the fifth degree and models with basic splines with knots at various positions (between 20 and 50 km distance). Model fit was compared based on the Akaike information criterion (AIC), and the models with lowest AIC were selected. The fit of selected models was compared to the observed proportion of cases who attended surveillance hospitals at different distances (moving average over a distance window of 25 km). We estimated the proportion of the population living >30 km and >50 km from a surveillance hospital using gridded population density estimates of 100 × 100 m resolution.
The spread of infectious diseases strongly depends on how habitat characteristics shape patterns of between-host interactions,. In particular, habitat heterogeneity influences patterns of between-individual contacts and hence, disease dynamics,. For example, “habitat hotspots”, sites that attract individuals or social groups over long distances, can be visited by a large subset of a population. Around hotspots, between-individual contact rates often increase in frequency, which amplifies disease transmission. In humans, schools and working places are typical examples of hotspots and have been shown to accelerate the spread of measles, influenza and SARS,,. Thus, limiting transmission at hotspots has become a promising strategy for mitigating epidemics (e.g., influenza) although the efficiency of such strategies also depends on the role hotspots plays relative to other sources of local transmission (e.g., influenza,)
In wild animal populations, high quality feeding spots (e.g., fruit trees), breeding sites, waterholes or sleeping sites can exacerbate direct physical contacts. Empirical and theoretical studies on the epidemiological importance of habitat hotspots have mainly focused on how the spatial aggregation of animals favors disease transmission at the hotspot itself,. For example, the aggregation of wild boar at watering sites significantly increases the transmission of tuberculosis-like lesions. However, inter-individual contacts may not always significantly increase at the hotspot itself. This is for example the case of habitat hotspots that some animal species only visited occasionally, such as some mineral licks,. Also, animals present at the same time at a particularly large hotspot may not be close enough to each other to transmit infectious diseases. This is the case of large forest clearings, or large waterholes. Finally, species such as primates and ungulates might avoid defecating in hotspots of high food resources, limiting the transmission of fecal-oral parasites at hotspots,.
When disease transmission does not occur at the hotspot, it can still occur at a certain distance from the hotspot. This phenomenon has received little attention so far. Specifically, infective contacts may be observed when infectious individuals travel to the hotspot and cross the territory of susceptible individuals and, reversely, when susceptible individuals cross the territory of infectious individuals. This second type of transmission may be prominent when the disease reduces the mobility of sick individuals (i.e., sickness behavior,,). For example, in humans, sick individuals often stay home, which alters disease dynamics,. Sick wild animals also commonly reduce their rate of search for food or water. Such transmission may particularly apply to parasites that can survive in the environment (e.g., gastrointestinal parasites) for which the spatial overlap of the home ranges of sympatric hosts favors transmission.
To investigate these transmission mechanisms, we developed an agent-based model exploring patterns of disease spread in a large closed population composed of territorial social groups, in which one or more hotspots influence group movement patterns, but where direct disease transmission at the hotspot itself is negligible. Our hypothesis is that terrestrial animals necessarily cross conspecifics' home ranges on their way to a hotspot, which modifies the contact network of the population and may subsequently alter disease transmission. We assumed that between-group disease transmission can occur both between groups having neighbouring territories and between groups travelling to a hotspot and groups whose territories are crossed en route. We also assumed that only groups which territory lies within a certain distance from the hotspot (further referred as “radius of attraction”) can visit it, and that their visitation rate decreases as this distance increases.
The relationship between the radius of attraction and the disease dynamics was then investigated under two scenarios: i) when groups including sick individuals do not travel to the hotspot, and ii) when these groups still travel to the hotspot. The first scenario corresponds to the case of virulent parasites that can strongly decrease the mobility of infected individuals, such as Ebola virus in western lowland gorillas, whereas the second scenario applies to pathogens that do not strongly modify the behavior of their host, such as some gastro-intestinal macro-parasites and bacteria. Under both scenarios, we investigated the relationship between the disease attack rate and the hotspot radius of attraction, identified the groups in the population that have the highest risk of infection and explored the relationship between the number of hotspots and the magnitude of an epidemic.
Included in the MDSS reports are disease statistics by county for various viruses, and certain areas of the state are more commonly affected by viral disease than others. Fig. 4 shows heatmaps for cases of four diseases (GI illnesses, influenza-like illnesses, hepatitis A virus, and norovirus) for each Michigan county. Variation in spatial distribution of diseases can be observed in Michigan, with GI illnesses concentrated in the southwest portion of the state, whereas the eastern portion of the state is most affected by hepatitis A.
Because MDSS issues weekly reports on disease statistics, temporal trends can also be observed for the illnesses in question. Fig. 5 displays the number of disease cases by month for the state of Michigan in the year 2017 for GI illnesses, influenza-like illnesses, hepatitis A virus, and norovirus. GI illness and influenza norovirus are all more prevalent in the winter and spring months. Hepatitis A virus cases are more common in the latter half of the year, but there is relatively little annual variation as compared to the other diseases in question.
Since the outbreak of SARS in 2003 the public health system in China has improved due to all levels of governments’ increased investment in disease control and prevention. The health status of the Chinese people has also improved. However, infectious diseases still remain a major cause of morbidity and mortality, and this may be exacerbated by rapid urbanization and unprecedented impacts from climate change. Although infectious diseases in China have been significantly reduced over recent decades, China’s current capacity to manage emerging and re-emerging infectious disease outbreaks is facing formidable challenges. A timely, streamlined, well-funded and efficient disease reporting and surveillance system is essential to monitor the threat of potential epidemics, which may not only affect population health in China but may also have wider implications for global health. In order to deal with future infectious disease threats effectively and promptly, comprehensive prevention and response strategies, which integrate a variety of complementary actions and measures, are needed. More research about infectious diseases, urbanization, climate change, and changing demographics needs to be conducted to support efforts to build China’s capacity to control and prevent the spread of emerging and re-emerging infectious diseases in the future.
The acute phase of diseases had the highest impact on the total burden (76%) (see Supplement 4). This was the result of the outcome trees that modelled case fatality proportions (CFP) as a direct risk to the acute infection. The high share of YLLs (72% of total DALYs, see Table 2) compared with YLDs was due to the limited amount of time lived with a disability, which is typical for infectious diseases.
Communicable disease is one of the leading causes of death worldwide. Lower respiratory infections were responsible for 3.0 million deaths in 2016 according to the World Health Organization (WHO), and diarrheal infections contributed to another 1.4 million deaths in the same year. Viral diseases contribute to these categories; influenza, coronavirus, and adenovirus are all considered lower respiratory infections, and viruses such as rotavirus can cause diarrheal disease. Viral disease outbreaks occur often, with WHO reporting outbreaks of influenza, coronavirus, hepatitis E, yellow fever, Ebola virus, Zika virus, poliovirus, dengue fever, and chikungunya in 2017 alone, located in countries all over the world such as Brazil, Chad, China, France, Italy, Saudi Arabia, and Sri Lanka. Moreover, environmental factors such as water, soil, and zoonotic vectors such as mosquitos and animals have been cited as important contributing factors to viral outbreaks.
WHO gathers surveillance statistics for specific viruses and estimates between 290,000 to 650,000 annual deaths from influenza, greater than previous estimates. Data from February 2018 indicated that the disease burden of influenza was highest in north and east Africa, South America, and Europe. Data from the WHO Mortality Database shows over 100,000 deaths from viral hepatitis since 2012 throughout the world. Outbreaks of gastrointestinal disease are also common around the world. Rotavirus, for example, is associated with high rates of pediatric mortality; rotavirus infection was found to be responsible for approximately 453,000 pediatric deaths in 2008 worldwide, accounting for 5% of all deaths in children younger than five years. Viral disease also disproportionately impacts poorer communities around the world. The aforementioned rotavirus study determined that over half of the pediatric rotavirus deaths worldwide occurred in just five developing nations (Democratic Republic of the Congo, Ethiopia, India, Nigeria, and Pakistan). Academic studies assessing global disease burden also report substantial burden due to viral disease. One study investigating global foodborne disease burden reported approximately 684 million disease cases and 212,000 deaths due to norovirus globally for the year 2010, the largest for any pathogen studied. The same study found hepatitis A virus responsible for approximately 47 million illnesses and 94,000 deaths in 2010.
Beyond diseases arising from direct infection, there are other secondary diseases associated with viruses, such as cervical cancer, which is strongly associated with papillomavirus. Other viruses have also been linked to increased incidences of heart disease and kidney disease, particularly in immunocompromised patients. Additionally, it is thought that the true impact of viral disease is underestimated. Many disease outbreaks are reported to be caused by agents of unknown etiology, and some of these outbreaks are suspected to be viral in origin. A One-Health approach could assist in discovering the origin of these disease outbreaks.
In the United States, the Centers for Disease Control (CDC) publish surveillance statistics regarding the rate and occurrence of disease for a number of human viruses, including influenza, adenovirus, hepatitis A virus, rotavirus, and West Nile virus. Annual summaries of these surveillance statistics are published in various forms from the CDC. The Summary of Notifiable Diseases (SoND) is an annual report containing information on those diseases for which “regular, frequent, and timely information regarding individual cases is considered necessary for the prevention and control of the disease or condition”, a list of which is updated regularly by the CDC. Viruses reported in the SoND include hepatitis A virus, West Nile virus, and Dengue virus. The CDC also maintains the National Outbreak Reporting System (NORS), which includes information on the number of disease cases and outbreaks for a number of infectious agents, including norovirus, rotavirus, and sapovirus. Influenza statistics are reported most frequently by the CDC via published FluView Weekly Influenza Surveillance Reports, documenting the number of cases of influenza and influenza-like illnesses in the United States. Each of these sources includes both monthly and geographic data regarding disease cases. This allows for the analysis of viral disease trends on both a temporal and spatial basis, many of which are unique from one virus to another [,,,,,,].
Most DALYs, around 60%, were due to infections occurring in males. Considering more detailed results presented in Supplement 4, diseases such as TB, HIV/AIDS, Legionnaires’ disease, were found to impact mostly men while chlamydia and gonorrhoea had a higher burden in women.
When considering DALYs over the total population, 11% occurred in children less than 5 years of age, 15% in individuals less than 15 years of age and 24% in individuals aged 65 years and over (see Supplement 4); most DALYs were found in age groups between 25 and 49 year of age (Figure 5). However, when considering the age group-specific DALYs per 100,000 population of the age group, those with the highest overall burden were infants under one year of age and individuals 80 years of age and over (Figure 6).
Compared with the age groups of between 15 and 64 years of age (adults) and 65 years of age and over (elderly population), the total burden of disease in the population under 15 years of age is lower (Figure 7). The diseases with the highest burden in the under 15 years age group are HBV infection, influenza, IHID, IPD and invasive meningococcal disease (IMD). HIV/AIDS, TB and influenza are the diseases with the highest burden in the adult population, whereas influenza, IPD and TB have the highest impact in the elderly population.
The burden of viral disease is a global challenge, and the surveillance and reporting of viral disease is one way in which to manage and mitigate outbreaks. In the United States, the Centers for Disease Control (CDC) publish surveillance statistics regarding the rate and occurrence of disease for a number of human viruses, and annual summaries of these surveillance statistics are published in various forms. The Summary of Notifiable Diseases (SoND) is an annual report containing information on those diseases for which “regular, frequent, and timely information regarding individual cases is considered necessary for the prevention and control of the disease or condition”, a list of which is updated regularly. The CDC also maintains the National Outbreak Reporting System (NORS), which includes information on the number of disease cases and outbreaks for a number of infectious agents, including certain viruses. Influenza statistics, meanwhile, are reported most frequently by the CDC via published FluView Weekly Influenza Surveillance Reports, documenting the number of cases of influenza and influenza-like illnesses in the United States. In assessing national viral disease burden, it is necessary to analyze data from all of these sources.
Fig. 1 presents the number of disease cases by month for influenza A as reported by FluView, West Nile virus and hepatitis A virus as reported by SoND, and norovirus, sapovirus, and rotavirus as reported by NORS from 2012 to 2016 [,,,,,,]. Each of the six viruses exhibit different times of year in which disease cases are more prevalent. Insect-transmitted viruses such as West Nile virus are more common in the warmer months from July to September. Meanwhile, the waterborne viruses (norovirus, sapovirus, rotavirus, and hepatitis A virus) all exhibit different trends. Perhaps most notable is the distinction between norovirus, which is most common in the winter from January to March, and sapovirus, which is most common in autumn from September to November. Norovirus and sapovirus are closely related, both being members of the Caliciviridae family, yet they have strikingly different seasonal infection trends. Hepatitis A virus, on the other hand, does not show significant variation throughout the year. Rather, rates of infection are relatively constant from one month to the next.
In addition to temporal variations, virus outbreaks also exhibit spatial variations, with certain areas being more commonly affected than others. The aforementioned CDC sources also publish information regarding the disease cases for each individual state. Fig. 2 presents heatmaps of disease cases relative to state population for the six viruses mentioned above. West Nile virus appears to be more prevalent in the plains states of the central United States, while norovirus is most common in the Midwest and New England. Moreover, there is no significant spatial differentiation for hepatitis A virus from one region to another, mimicking its temporal trends. Rotavirus and sapovirus, meanwhile, tend to be concentrated in specific states, suggesting that outbreaks are the most common drivers of occurrence of these diseases. It is important to note, however, that these statistics are only a measure of reported cases, and that the actual incidence of viral disease could be significantly higher than the reported statistics indicate. For example, the CDC estimates that the rates of hepatitis A virus are approximately twice as high as reported incidence rates indicate.
Viral disease data have also been collected for the State of Michigan. Viral disease has been demonstrated to impact human, animal, and environmental health within the state of Michigan. Numerous human outbreaks due to multiple viral agents have been reported. These outbreaks include coronavirus in Lenawee County in 1966, norovirus in Macomb County in 1979 and in Ottawa County in 2008, hepatitis A virus in Calhoun and Saginaw Counties in 1997, and West Nile virus in Kent County in 2002. Michigan has also been in the midst of an outbreak of hepatitis A virus since 2016. Illustrated in these examples is both the variety of human viral diseases that have impacted the state as well as that different areas of the state are subject to outbreaks.
Numerous governmental agencies publish data regarding clinical cases of disease both spatially and temporally. In addition to the published federal data, individual states publish disease surveillance statistics, such as the Michigan Department of Health and Human Services (MDHHS). MDHSS maintains the Michigan Disease Surveillance System (MDSS) which publishes weekly disease reports on a number of communicable diseases. Data taken from MDSS reports show an increase in viral disease over the past five years, as shown in Fig. 3. For this paper, gastrointestinal (GI) illnesses, influenza-like illnesses, hepatitis A illnesses, and norovirus illnesses are selected. While some GI illnesses and influenza-like illnesses may be caused by bacterial pathogens, a large percentage of GI illnesses and influenza-like illnesses are expected to be of viral origin and all hepatitis and norovirus illnesses are of viral origin. These diseases have been selected for investigation since they have different exposure pathways. Influenza illnesses may be zoonotic but are not waterborne. Hepatitis A illnesses are waterborne but are not zoonotic. Norovirus is commonly foodborne, it may be waterborne, and it is not typically zoonotic. GI illnesses may be both waterborne and zoonotic and may be caused by viruses, bacteria, or paracites.
Viral disease outbreaks have also affected animals in Michigan, including viral diarrhea in cattle, eastern equine encephalitis virus in deer, and an outbreak of a novel calicivirus in rabbits. According to the USDA report on death loss in U.S. cattle and calves (2015), 31.8% of non-predator cattle deaths and 42.3% of non-predator calf deaths were due to digestive or respiratory causes. These figures are amplified in the state of Michigan; the percentages are 37.8% and 66.3% respectively, equating to approximately 9027 cattle deaths and 27,926 calf deaths in the state during 2015. While the report does not specify the etiological nature of the deaths, a portion of these illnesses are due to viral causes, illustrating the potential burden of viral disease on animals. The Michigan Department of Agriculture & Rural Development (MDARD) also publishes annual statistics on reportable animal diseases. The MDARD report from 2017 includes many viral animal disease cases, including 373 cases of bovine leukemia virus, 160 cases of caprine arthritis encephalitis, 17 cases of porcine reproductive and respiratory syndrome virus, 7 cases of swine enteric coronavirus, 9 cases of canine influenza, 7 cases of eastern equine encephalitis, 10 cases of equine herpesvirus, and 15 cases of West Nile virus in equines.
Moreover, viruses have been detected in environmental samples in Michigan. Human enteric viruses have been detected in the effluent of multiple Michigan wastewater treatment plants, which is released into surrounding surface waters. Adenovirus and other human viruses have also been detected at public recreational beaches in Michigan, leading to beach closures. Numerous environmental factors may contribute to the likelihood of infectious disease in certain areas or time periods, including but not limited to land use, precipitation, and population density. Land use is relevant to determine the environmental state of the area, and can be impactful during runoff events. Precipitation levels inform where these runoff events may occur. Population and population density can affect the spread of viral disease and can also be used to normalize disease levels from one county to another. Other factors can be used to further characterize land use, such as information related to agricultural activity. Variables such as livestock population can not only illustrate the level of agricultural activity in an area, but also illustrate the expected quality of nearby surface water after runoff events.
Because viral infection is able to spread to humans from the environment, animals, and other humans, the One-Health framework is ideal to investigate the critical pathways through which viruses are transported and transmitted. Data collection related to human, animal, and environmental health is crucial to attain preliminary information for the identification of these critical pathways. This information can help to illuminate the parameters that affect the spatial and temporal patterns of disease. The goal of this study is to present an example preliminary data collection and analysis approach for the state of Michigan.
Emergence and reemergence of infectious diseases occur over time. Prior to causing an epidemic, infectious disease agents go through various stages of adaptation to access or acquire pathogenic characteristics in a new host. Specific processes such as gene mutation, genetic recombination, or reassortment as well as factors that compel microbial agents to change reservoir hosts constitute opportunities for infectious agents to evolve, adapt to new hosts in new ecological niches, and spread easily [18, 19]. A number of factors contribute to this adaptation and consequent disease emergence. The complex interactions between infectious agents, hosts, and the environment are key.
Specifically, factors affecting the environment include depletion of forests, expansion and modernization of agricultural practices, and natural disasters such as floods. These potentially lead to changes in microbial ecological niches and fuel microbial adaptation to human host [20, 21]. Sociodemographic factors such as increase in population density, falling living standards, decline of infrastructure, human travel, conflicts and social instability, and killing of wild animals for meat all lead to increase in host-microbe contact, which facilitate infections in humans [22–25]. There are also some pathogens whose emergence is as a result of deliberate human action. These are those employed as biological weapons for destruction and so their emergence is “deliberate.”
Besides host and environmental factors, changes or mutation in the genome of a pathogen, which occurs as a result of exposure to chemicals and antimicrobial agents (e.g., antibiotic), may lead to gene damage and emergence of drug resistant pathogen variants that could cause new disease. Thus, human, microbial, and environmental factors constitute major causes of infectious disease emergence and the virulence or pathogenic potential depends on a complex combination of these factors. However, generally, emerging infectious diseases caused by viral pathogens are responsible for the greatest proportion of the EID threat, having caused about two-thirds of the infectious disease burden and usually characterized by very high epidemics. Examples are Filoviruses, Ebola, and Marburg [28, 29].
Spatial features of the landscape such as habitat hotspots can profoundly influence the spread of infectious diseases,. Our model extends previous studies focusing on transmission at the hotspot, and reveals that hotspots can also strongly alter disease transmission by generating infective contacts between animals travelling towards or from the hotspot and animals whose territories are traversed. Our results show that even when sick groups stay in their territory, hotspots may increase the size of an epidemic. When infected animals cease to visit the hotspot, groups ranging at intermediate distances to the hotspot are the most vulnerable. We also found that the epidemiological impact of hotspots extends far beyond the subset of the population that visits it; even groups having no contact with those visiting the hotspot display elevated risks of infection. Finally, our model predicts that when groups visit their nearest hotspots, the epidemiological impact of hotspots is most severe when the number of hotspots is intermediate.
Hotspots impact disease transmission via a combination of both local between-neighbour and long-range traveler-resident transmissions, which is characteristic of a small-world network. Disease dynamics in our model resemble those in a classic small-world network in several aspects. First, the attack rate increases with long-distance interactions, determined by the hotspot radius of attraction (Fig. 2). Second, new foci of infection established by long-distance traveler-resident contacts only spread when the local transmission rate, between neighbours, is sufficiently high. This phenomenon extends the influence of the hotspot beyond the radius of attraction (Fig. 4). Finally, as in small-world networks, all groups within the hotspot radius of attraction were infected almost at the same time. Thus, habitat hotspots potentially play a significant role in fuelling disease outbreaks, much like other natural mechanisms that generate small-world networks, such as the movement of vectors between plants,.
We find that hotspots are expected to influence disease dynamics significantly, even when infected groups do not travel to the hotspot at all. However, in this case, the hotspot effect strongly decreases as the distance between disease introduction and the hotspot increases. The reduction of mobility in infected groups also generates an unexpected spatio-temporal pattern: groups ranging at intermediate distance from the hotspot have the highest risk of infection, even if the disease is introduced immediately next to the hotspot. This counterintuitive result highlights the importance of understanding the behavioral effects of disease in wild animal populations. For example, as in humans, predicting the impact of hotspots on disease dynamics will strongly depend on understanding whether infectious individuals still travel to hotspots because disease symptoms appear after an infectious state (e.g., influenza H1N1,), or whether infectious individuals do not visit hotspots because disease symptoms appear before the infectious state (e.g., SARS,). Furthermore, our results suggest that when transmission does not directly occur at hotspots, disease control measures targeting groups residing around the hotspot might not necessarily be the most efficient ones. Further simulation work is needed to identify optimal disease control measures.
The habitat of wild animal populations often includes more than one hotspot. For example, the habitat of terrestrial mammals can include a small number of high-value hotspots attracting dozens of groups (e.g., salt licks or forest clearings) and more numerous low-value hotspots attracting only a few groups (e.g., fruiting trees). Our model reveals that, when groups are assumed to travel to their nearest hotspot, the impact of disease outbreaks is a bell-shaped function of the number of hotspots (Fig. 5). This result challenges the hypothesis that the number of hotspots and disease prevalence will correlate positively, and could be used to optimize strategies for controlling disease in wild animal populations. Thus, wildlife managers may consider increasing, rather than decreasing, the number of water holes in order to reduce the number of highly-connected individuals or social groups, and hence the impact of an outbreak. However, additional studies are needed to determine if our result still holds when each animal visits more than one hotspot.
The values of the parameters of our model can be estimated from empirical data. The relationship between the distance from a group's territory and the hotspot visitation rate can be estimated using capture-mark recapture and telemetric data, between-group contact rates can be estimated from direct observation or telemetric data, and plausible distributions of disease transmission rates can be found in the literature. The step length of the biased random walk is assumed to have a fixed value (here, 0.25 times the size of a territory). This parameter does not need to be estimated accurately since it is redundant with another parameter, the traveler-resident contact rate, which is allowed to vary. Thus, the model can be applied to a broad range of host-parasite systems, from primate groups travelling to waterholes on a daily basis, to large mammals visiting every few weeks mineral-rich areas,,. In our model, the impact of the hotspot is particularly sensitive to the ratio between the local and the traveler-resident between-group transmissions. When the local between-neighbour transmission is high compared to the traveler-resident transmission, the impact of the hotspot is minimal.
We considered two discrete transmission scenarios, the Sick-travel and the Sick-stay scenarios. However, intermediate scenarios are also possible. For example, infected groups may fission such that only healthy individuals travel to the hotspot. In this case, we expect that although the overall disease transmission will increase compared to the pure Sick-stay scenario, the spatial pattern of the disease impact will be qualitatively similar to that observed for the Sick-stay model.
In this study, we have shown how transmission occurring around habitat hotspots influences disease transmission patterns, while previous studies have focused on disease transmission occurring at the hotspot itself. In some ecological systems, both transmission modes may coexist. For example, some fecal-orally transmitted parasites can infect both the soil and waterholes, and spore-forming bacteria such as Bacillus anthracis can persist for extended periods of time in animal carcasses, water and soil. Additional works are needed to understand such epidemiological systems.
We ran the algorithm on each outbreak year using only patients who tested negative for all four of influenza, RSV, parainfluenza, and hMPV. Because they were tested, we assume they have an ILI. However, since all of their tests were negative, their diagnoses were indeterminate. That is, they have some kind of ILI but do not have any of the modeled diseases.
Fig 3 shows the (logarithm of the) daily odds of the presence of an unmodeled disease in the monitor window for outbreak year 2014-2015. DUDE begins computing odds on day 93 (September 1). The odds of the presence of an unmodeled disease slowly increased and was greater than 1 on day 106 (September 14, 2014) indicating that it was more likely than not that an unmodeled disease was present. After day 106 the odds of the presence of an unmodeled disease increased dramatically. An examination of records in the monitor window at that time showed a prevalence of patients with wheezing, chest wall retractions, runny nose, respiratory distress, crackles, tachypnea, abnormal breath sounds, headache, stuffy nose, and dyspnea. (These are the findings that were at least 25% more likely to occur in a patient in the monitor window than one in the baseline window and were present in at least 10% of the patients in the monitor window).
During this time period, the CDC identified an outbreak of Enterovirus D68 (EV-D68). In mid-August 2014 hospitals in Missouri and Illinois notified the CDC of an increase in admissions of children with severe respiratory illness. By September 8, 2014 officials at Primary Children’s hospital in Salt Lake City, Utah suspected the presence of EV-D68, and by September 23, 2014 the CDC confirmed the existence of EV-D68 in Utah. Since August 2014, the CDC and states began doing more testing for EV-D68, and have found that EV-D68 was causing severe respiratory illness in almost all states. Symptoms of EV-D68 include wheezing, difficulty breathing, runny nose, sneezing, cough, body aches, and muscle aches. (Severe symptoms of EV-D68 may also include acute flaccid paralysis, but this is not among the symptoms used by DUDE).
Fig 4 shows the results of running the algorithm on patients who tested negative for all four of influenza, RSV, parainfluenza, and hMPV patients for outbreak years 2010-2011 (top) through 2014-2015 (bottom).
The present study screened the occurrence of parvovirus DNA and the feline host-immune status in a cat population. Asymptomatic and symptomatic cats sampled in Sardinia (Italy) during 2011–2012 were tested for the presence of both FPV and CPV DNA in WBC using qPCR, and the partial VP2 gene of the viruses identified was characterised. Parvoviruses have commonly been titrated in the faeces of infected animals, insofar as the viruses shed in faeces reflect virus replication; the Authors chose to analyse the WBC for the presence of viral DNA as, in addition to the intestinal crypt cells, bone marrow and other lymphoid tissues are also a major target for parvoviruses in both dogs and cats. Furthermore, since parvovirus can frequently be isolated in infected cats, even in the presence of high virus-neutralising antibodies [15, 17], antibody titres against parvovirus were established in the sera of positive cats using an HI assay.
Nine (16.7%) out of a total of 54 cats tested positive for parvovirus DNA with viral DNA quantities ranging from 100 to 102 copies/μl of extract, demonstrating that the viral genome was detectable, although at low levels, in the WBC of a relatively large number of cats. All the cats which tested positive for parvovirus DNA had antibodies against parvoviruses. Positive cats included healthy and diseased cats. Although sick cats had a potentially greater probability of being persistently infected, none of the samples from cats showing signs of gastroenteritis tested positive.
The presence of FPV and CPV DNA in the faecal and peripheral blood samples of healthy cats has previously been reported [3, 12, 15–17], raising important questions regarding the role of cats in the epidemiology of parvoviruses. In our study, the absence of clinical signs consistent with parvovirosis in the cats which tested positive, together with the low amount of viral DNA detected, suggested that the infection was asymptomatic or that residual viral DNA remains in the organism after recovery from acute infection. Furthermore, the detection of parvoviral DNA in WBC reveals the presence of the virus in the bone marrow or in other lymphoid tissues which might reflect chronic or latent infection. The detection of CPV DNA in apparently healthy domestic cats confirmed a previous survey in which a high prevalence (37%) of CPV in apparently healthy domestic cats living in rescue shelters was identified. Canine parvovirus-like DNA was also detected in the tissues of wildlife carnivores which had no clinical signs of active infection and, therefore, it was likely that this virus caused latent or persistent infection not only in domestic cats. Animal parvoviruses, such as Rodent protoparvovirus and Aleutian mink disease parvovirus, have been shown to persist in their host [27, 28]. Persistence is a common feature also for human parvovirus B19 (B19V) infection: B19V parvoviral DNA has been documented in a wide range of tissues and the bone marrow of asymptomatic adults, although the majority of people harbour parvoviral DNA in a form which does not actively replicate [30, 31].
Of the nine cats testing positive for parvovirus DNA, four showed FPV DNA, four CPV DNA (three CPV-2b and one CPV-2c), and cat 41/2011 showed unusually high genetic diversity and evidenced DNA belonging to two species of parvovirus in the same patient.
The pathogenicity of CPV variants for cats is not fully understood. Some studies have suggested that CPV had the same pathogenic potential as FPV in cats [3, 32–35]; in other studies, clinical signs were not observed in infected animals, with the exception of transient leukopenia [36, 37]. These results led to the speculation that CPV, compared to FPV, can most frequently cause asymptomatic and persistent infection in cats, even if additional studies are clearly needed to fully understand the potential of cats as CPV carriers. In our study, an equivalent prevalence of FPV and CPV was found in the samples examined; this result might be related to the type of cat population sampled, which consisted mainly of healthy cats and cats showing clinical signs not related to parvovirosis. Alternatively, it could be due to the biological matrix analysed since parvoviruses have commonly been investigated in the faeces of infected animals; instead, in our survey the WBC were analysed.
The rates of variation of the FPV and CPV nucleotide sequences analysed in this study were similar, although genetic diversity in the FPV sequences was generated primarily by synonymous mutations which did not result in amino acid substitutions. This result was congruent with the evolutive behaviour of FPV which, since its emergence in 1920, has not undergone significant changes in antigenic and biological properties. Feline panleukopenia virus varied at a slow rate by random genetic drift and it maintained host-specificity. Instead, in the CPV sequence data set, non-synonymous mutations were predominant. This finding is compatible with the pattern of evolution observed for CPV. Since its emergence in the late 1970s, CPV evolution has been driven by strong positive selection, giving rise to new antigenic variants which have replaced the original type.
An unusual genetic complexity was reported for sample 41/2011, with six different viral DNAs ascribable to two distinct species of parvovirus, FPV and CPV type 2c. Although co-infection by more than one parvovirus species is a rare event, it has already been described in a cat simultaneously infected by FPV and CPV-2a.
Carnivore protoparvoviruses show an estimated annual substitution rate on the order of 10− 4 to 10− 5 whereas the mutation frequency detected in sample 41/2011 was on the order of 2.8 × 10− 3, a value which determines the quasispecies distribution in RNA virus populations. Carnivore parvoviruses are very prone to genetic evolution, showing substitution rates similar to those of RNA viruses, with values of approximately 10− 4 substitutions per site per year. This result, together with the detection of CPV-2c, which has already been reported in multiple infections of high genetic complexity [3, 5, 39], confirmed that co-infection with different species of parvovirus in feline hosts led to a high genetic variability and to the potential emergence of new viruses.
The presence of distinctive mutations between the FPV DNA sequences detected and the sequences of modified live FPV vaccine strains available, together with the lack of information regarding the vaccination history of the cats sampled, allowed the Authors to exclude the possibility that DNA from vaccine strains was detected and did not allow speculation regarding the persistence of modified live vaccine strains in the cats sampled. However, viraemia persisting up to 24 days post vaccination has been reported in dogs vaccinated with modified live canine parvovirus.
An emerging infectious disease (EID) can be defined as ‘an infectious disease whose incidence is increasing following its first introduction into a new host population or whose incidence is increasing in an existing host population as a result of long-term changes in its underlying epidemiology'.1 EID events may also be caused by a pathogen expanding into an area in which it has not previously been reported, or which has significantly changed its pathological or clinical presentation.2
Mostly, infectious disease emergence in humans is caused by pathogens of animal origin, so-called zoonoses.2,3,4,5 Likewise, cross-over events may occur between non-human species including between domestic animals and wildlife, and such events also involve transmission from a reservoir population into a novel host population (spill-over).5,6,7 Emergence in a novel host, which includes spill-over/zoonoses, has been extensively studied. An elaborate framework featuring the subsequent stages in the emergence process of a species jump has already been developed, describing how an established animal pathogen, through stages of spill-over and lengthening of the transmission chain in the novel host, may evolve all the way up to an established and genetically consolidated pathogenic agent.8,9,10 However, as implied by the above broader definition of EID, other categories can be distinguished in addition to emergence in a novel host, including disease outbreaks in an existing host or the emergence of a disease complex beyond the normal geographic range.
Here, we will argue that changes in host range, in pathogen traits displayed in the same host, and the geographic distribution of a disease complex, form three distinct sets of complementary and only slightly intersecting disease emergence scenarios. Together, these scenarios present the full picture and range of possible disease emergence dynamics. Hence, we categorize EIDs into three main groups, with emergence of (i) a pathogen in a novel host; (ii) a pathogen with novel traits within the same host; and (iii) a disease complex moving into a novel geographic area. Human actions that modulate the interplay between pathogens, hosts and environment are at the basis of almost all EID events, although the exact drivers and mechanisms differ. For each of the three groups, we will argue how the emergence process is driven by specific sets of causal factors, discuss the changes in disease ecology and transmission and elaborate on the invasion dynamics and on the characteristics of pathogens that are dominant in each group. Such structuring of the myriad of EID on the basis of the changes in the interplay between pathogens, hosts and environment will assist in better understanding of specific EID events and in designing tailored measures for prevention and prediction. Moreover, the framework contributes to understanding the effects of human actions that pave the way for the three distinct emergence scenarios. We propose that the resulting framework applies not just to pathogens affecting humans and animals in agriculture and natural ecosystems; it may be usefully applied also for pest and disease emergence in aquaculture, plant production and insect rearing.
Viruses that infect humans can be both specific to humans and zoonotic in nature. Human viruses are categorized as those that exclusively infect humans and are transmissible from the environment to humans or from human to human. Zoonotic viruses, meanwhile, are defined as viruses “which are naturally transmitted between vertebrate animals and man”. Zoonotic viruses can also be further split into direct and indirect categories. Direct zoonoses involve infection via direct contact between humans and animals, such as skin contact, a bite, or ingestion of tissue. Indirect zoonoses, meanwhile, require a vector or vehicle for transmission of the virus between humans and animals.
Viruses can also be divided to categories based on their water-related transmission potential. This classification was put forth by Bradley (1977), splitting water-related infections into four main categories: water-washed infections (diseases arising from poor hygiene) and water-based infections (infections from worm parasites that spend their life cycle in an aquatic environment), as well as waterborne infections and infections with water-related insect vectors, the latter two designations being most relevant when discussing water-related viruses [,,]. The foremost category is that of waterborne viruses, in which a virus is present in water and infection occurs via ingestion of the contaminated water source. Waterborne viruses will often enter the water source due to fecal contamination, making waste and wastewater management a critical pathway for tracking the spread of viral waterborne disease. The second important category of water-related viruses are those with water-related insect vectors. This includes viruses transmitted by insects that breed in water, such as mosquitos, which carry numerous significant human viruses, such as Zika virus and West Nile virus. In areas where primary water sources may be infested with these insect vectors, this is critical pathway for the spread of viral disease. Finally, another potential transmission pathway for water-related disease is the aerosolization of contaminated water, in which viruses capable of respiratory transmission are inhaled following aerosolization.
With these categories of zoonotic and water-related viruses in place, there is potential for crossover among them; some viruses may be both zoonotic and water-related. In a report on waterborne zoonoses in 2004, WHO put forth criteria for determining if a pathogen meets these qualifications: the pathogen must spend part of its life cycle within animal species, it is probable the pathogen will have a life stage that will enter water, and transmission of the pathogen between humans and animals must be through a water-related route. If a virus meets all of these, it can be classified as a zoonotic water-related virus.
Table 1 lists several human viruses of concern (including all viruses included in SoND) and classifies them according to the aforementioned categories. As mentioned above, a primary exposure pathway to viral disease for humans is wastewater. The ability to detect viruses in wastewater is therefore critical for investigation via One-Health, and this information is also summarized in Table 1. As noted in the table, several of these viruses fall under multiple categories, being both water-related and zoonotic. For instance, enteroviruses, hepatitis E virus, and rotaviruses are all classified as waterborne viruses, and each of them has been reported to have potential zoonotic properties as well, as cases of these viruses have been observed in animals. Additionally, a number of viruses are zoonotic due to their transmission between mosquitos and humans, such as West Nile virus, Zika virus, and Dengue virus [,,]. Zoonotic diseases comprise approximately 64% of all human pathogens, with viruses accounting for 5% of pathogens. Zoonoses are also responsible for 26% of the disease burden in low-income countries, whereas they only account for 0.7% in wealthier nations.
Moreover, many of the viruses listed in Table 1 have been reported as detected in wastewater or human excrement. This is important as it signifies that these viruses are present or potentially present in aquatic pathways. This is true even for viruses that are not typically designated as waterborne or water-related, such as influenza, herpesvirus, and papillomavirus.
Regarding animal viruses of concern, the U.S. Department of Agriculture (USDA) issues annual reports of the domestic status of reportable diseases put forth by the World Organization for Animal Health (OIE). Table 2 summarizes livestock viral diseases that were reported as present in the United States by the USDA. Many of the same viral families that affect humans are represented in this list, including Coronaviridae, Flaviviridae, Herpesviridae, Orthomyxoviridae, and Reoviridae. A few of the reportable viral animal diseases are also considered zoonotic, which are of even greater significance to human health.
The USDA also collects and maintains disease data for domesticated, agricultural, and wild animals, primarily via the National Animal Health Surveillance System (NAHSS). A number of viruses are investigated via NAHSS for various animals, including influenza A virus in swine, and herpesvirus and West Nile virus in horses. Annual reports regarding cases of equine West Nile virus in domesticated horses are published via NAHSS, making them a useful comparison to reported human cases of West Nile virus. In addition to domesticated animals, wild animals are also an important consideration, as wildlife has been shown to be a source of disease to both livestock and humans.
Parvoviruses are non-enveloped single-stranded DNA viruses which infect a wide range of mammalian species, including several members of the order Carnivora. The Carnivore protoparvovirus 1, belonging to genus Protoparvovirus, family Parvoviridae, subfamily Parvovirinae, includes several closely related autonomous viruses causing a range of serious conditions, especially in young animals: feline panleukopenia virus (FPV, the prototype virus of the former carnivore parvovirus), canine parvovirus (CPV), mink enteritis virus (MEV), and raccoon parvovirus (RaPV).
Feline panleukopenia virus has been known to be a cause of disease in cats since the beginning of the twentieth century, although there are other similar parvovirus species affecting cats, such as MEV and CPV. Natural infections in cats with CPV have been reported but FPV remains the most prevalent parvovirus causing disease in cats [2–4]. Since cats are susceptible to FPV and CPV 2a, 2b, 2c variants, superinfection and co-infection with multiple parvovirus strains associated with high viral genetic heterogeneity can occur with relatively high frequency in feline hosts [3, 5–7].
Parvoviruses commonly cause acute infection with high levels of viral shedding which generally ceases within 1–2 weeks post-infection, after the development of high titres of virus-neutralising antibody [8, 9]. Nevertheless, parvoviruses can be detected in faeces forup to 6 weeks after recovery, depending on the sensitivity of the diagnostic method used. Cats experimentally infected with FPV shed the virus in both urine and faeces up to day 41–42 post-infection with parvovirus persisting in the lungs and kidneys for more than 50 weeks in cats which have recovered. The detection of FPV and CPV variants in apparently healthy cats suggests that parvovirus infection may be common in some populations of clinically normal cats, and that asymptomatic cats may be able to shed parvovirus for prolonged periods of time [12–14]. Furthermore, the ability of FPV and CPV to persist in the peripheral blood mononuclear cells (PBMC) of cats irrespective of the presence of neutralising antibodies [13–17] and the presence of parvoviral DNA in the bone marrow of healthy cats, suggests that parvovirus may persist long term in the tissues of cats post-infection without causing clinical signs.
The aim of this study was to screen a population of 54 cats from Sardinia (Italy) for the presence of both FPV and CPV DNA within buffy coat samples. The DNA viral load, genetic diversity, phylogeny and antibody titres against parvoviruses were investigated in the cats testing positive to DNA parvoviruses.