Markets as drivers of selection for highly virulent poultry pathogens.

Theoretical models have successfully predicted the evolution of poultry pathogen virulence in industrialized farm contexts of broiler chicken populations. Whether there are ecological factors specific to more traditional rural farming that affect virulence is an open question. Within non-industrialized farming networks, live bird markets are known to be hotspots of transmission, but whether they could shift selection pressures on the evolution of poultry pathogen virulence has not been addressed. Here, we revisit predictions for the evolution of virulence for viral poultry pathogens, such as Newcastle's disease virus, Marek's disease virus, and influenza virus, H5N1, using a compartmental model that represents transmission in rural markets. We show that both the higher turnover rate and higher environmental persistence in markets relative to farms could select for higher optimal virulence strategies. In contrast to theoretical results modeling industrialized poultry farms, we find that cleaning could also select for decreased virulence in the live poultry market setting. Additionally, we predict that more virulent strategies selected in markets could circulate solely within poultry located in markets. Thus, we recommend the close monitoring of markets not only as hotspots of transmission, but as potential sources of more virulent strains of poultry pathogens.

Excess mortality associated with the COVID-19 pandemic during the 2020 and 2021 waves in Antananarivo, Madagascar.

INTRODUCTION: COVID-19-associated mortality remains difficult to estimate in sub-Saharan Africa because of the lack of comprehensive systems of death registration. Based on death registers referring to the capital city of Madagascar, we sought to estimate the excess mortality during the COVID-19 pandemic and calculate the loss of life expectancy. METHODS: Death records between 2016 and 2021 were used to estimate weekly excess mortality during the pandemic period. To infer its synchrony with circulation of SARS-CoV-2, a cross-wavelet analysis was performed. Life expectancy loss due to the COVID-19 pandemic was calculated by projecting mortality rates using the Lee and Carter model and extrapolating the prepandemic trends (1990-2019). Differences in life expectancy at birth were disaggregated by cause of death. RESULTS: Peaks of excess mortality in 2020-21 were associated with waves of COVID-19. Estimates of all-cause excess mortality were 38.5 and 64.9 per 100 000 inhabitants in 2020 and 2021, respectively, with excess mortality reaching ≥50% over 6 weeks. In 2021, we quantified a drop of 0.8 and 1.0 years in the life expectancy for men and women, respectively attributable to increased risks of death beyond the age of 60 years. CONCLUSION: We observed high excess mortality during the pandemic period, in particular around the peaks of SARS-CoV-2 circulation in Antananarivo. Our study highlights the need to implement death registration systems in low-income countries to document true toll of a pandemic.

Prioritizing COVID-19 vaccination efforts and dose allocation within Madagascar.

BACKGROUND: While mass COVID-19 vaccination programs are underway in high-income countries, limited availability of doses has resulted in few vaccines administered in low and middle income countries (LMICs). The COVID-19 Vaccines Global Access (COVAX) is a WHO-led initiative to promote vaccine access equity to LMICs and is providing many of the doses available in these settings. However, initial doses are limited and countries, such as Madagascar, need to develop prioritization schemes to maximize the benefits of vaccination with very limited supplies. There is some consensus that dose deployment should initially target health care workers, and those who are more vulnerable including older individuals. However, questions of geographic deployment remain, in particular associated with limits around vaccine access and delivery capacity in underserved communities, for example in rural areas that may also include substantial proportions of the population. METHODS: To address these questions, we developed a mathematical model of SARS-CoV-2 transmission dynamics and simulated various vaccination allocation strategies for Madagascar. Simulated strategies were based on a number of possible geographical prioritization schemes, testing sensitivity to initial susceptibility in the population, and evaluating the potential of tests for previous infection. RESULTS: Using cumulative deaths due to COVID-19 as the main outcome of interest, our results indicate that distributing the number of vaccine doses according to the number of elderly living in the region or according to the population size results in a greater reduction of mortality compared to distributing doses based on the reported number of cases and deaths. The benefits of vaccination strategies are diminished if the burden (and thus accumulated immunity) has been greatest in the most populous regions, but the overall strategy ranking remains comparable. If rapid tests for prior immunity may be swiftly and effectively delivered, there is potential for considerable gain in mortality averted, but considering delivery limitations modulates this. CONCLUSION: At a subnational scale, our results support the strategy adopted by the COVAX initiative at a global scale.

Madagascar Terrestrial Camera Survey Database 2021: A collation of protected forest camera surveys from 2007-2021.

Madagascar is a threatened global biodiversity hotspot and conservation priority, yet we lack broad-scale surveys to assess biodiversity across space and time. To fill this gap, we collated camera trap surveys, capturing species occurrences within Madagascar into a single standardized database. This data set includes nine distinct protected areas of Madagascar and encompasses 13 subprojects, 38 camera arrays, and 1156 sampling units (independent camera site per survey) within two important biodiversity eco-regions: western dry deciduous forest and eastern humid rainforest. Camera surveys were conducted from June 2007 to January 2021. The final data set includes 17 unique families of mammals (Bovidae, Canidae, Cheirogaleidae, Daubentoniidae, Equidae, Eupleridae, Felidae, Hominidae, Indriidae, Lemuridae, Lepilemuridae, Muridae, Nesomyidae, Pteropodidae, Soricidae, Suidae, Tenrecidae) comprising 45 species and 27 unique families of birds (Accipitridae, Acrocephalidae, Alcedinidae, Bernieridae, Brachypteraciidae, Caprimulgidae, Cisticolidae, Columbidae, Coraciidae, Corvidae, Cuculidae, Dicruridae, Mesitornithidae, Monarchidae, Motacillidae, Muscicapidae, Numididae, Phasianidae, Rallidae, Sarothruridae, Strigidae, Sturnidae, Sulidae, Threskiornithidae, Upupidae, Vangidae, Zosteropidae) comprising 58 species. Images were processed and verified by individual project data set creators and camera operation and species tables were then collated. The final product represents the first broad-scale freely available standardized formal faunal database for Madagascar. Data are available through this publication and at DOI: 10.5281/zenodo.5801806. These data will be useful for examining species-level and community-level trends in occurrence across space or time within Madagascar and globally, evaluating native and invasive species dynamics, and will aid in determining species conservation status and planning for at-risk species. There are no copyright restrictions; please cite this paper when using the data for publication.

Infectious disease in an era of global change.

The twenty-first century has witnessed a wave of severe infectious disease outbreaks, not least the COVID-19 pandemic, which has had a devastating impact on lives and livelihoods around the globe. The 2003 severe acute respiratory syndrome coronavirus outbreak, the 2009 swine flu pandemic, the 2012 Middle East respiratory syndrome coronavirus outbreak, the 2013-2016 Ebola virus disease epidemic in West Africa and the 2015 Zika virus disease epidemic all resulted in substantial morbidity and mortality while spreading across borders to infect people in multiple countries. At the same time, the past few decades have ushered in an unprecedented era of technological, demographic and climatic change: airline flights have doubled since 2000, since 2007 more people live in urban areas than rural areas, population numbers continue to climb and climate change presents an escalating threat to society. In this Review, we consider the extent to which these recent global changes have increased the risk of infectious disease outbreaks, even as improved sanitation and access to health care have resulted in considerable progress worldwide.

Cross-sectional cycle threshold values reflect epidemic dynamics of COVID-19 in Madagascar.

As the national reference laboratory for febrile illness in Madagascar, we processed samples from the first epidemic wave of COVID-19, between March and September 2020. We fit generalized additive models to cycle threshold (Ct) value data from our RT-qPCR platform, demonstrating a peak in high viral load, low-Ct value infections temporally coincident with peak epidemic growth rates estimated in real time from publicly-reported incidence data and retrospectively from our own laboratory testing data across three administrative regions. We additionally demonstrate a statistically significant effect of duration of time since infection onset on Ct value, suggesting that Ct value can be used as a biomarker of the stage at which an individual is sampled in the course of an infection trajectory. As an extension, the population-level Ct distribution at a given timepoint can be used to estimate population-level epidemiological dynamics. We illustrate this concept by adopting a recently-developed, nested modeling approach, embedding a within-host viral kinetics model within a population-level Susceptible-Exposed-Infectious-Recovered (SEIR) framework, to mechanistically estimate epidemic growth rates from cross-sectional Ct distributions across three regions in Madagascar. We find that Ct-derived epidemic growth estimates slightly precede those derived from incidence data across the first epidemic wave, suggesting delays in surveillance and case reporting. Our findings indicate that public reporting of Ct values could offer an important resource for epidemiological inference in low surveillance settings, enabling forecasts of impending incidence peaks in regions with limited case reporting.

Existing human mobility data sources poorly predicted the spatial spread of SARS-CoV-2 in Madagascar.

For emerging epidemics such as the COVID-19 pandemic, quantifying travel is a key component of developing accurate predictive models of disease spread to inform public health planning. However, in many LMICs, traditional data sets on travel such as commuting surveys as well as non-traditional sources such as mobile phone data are lacking, or, where available, have only rarely been leveraged by the public health community. Evaluating the accuracy of available data to measure transmission-relevant travel may be further hampered by limited reporting of suspected and laboratory confirmed infections. Here, we leverage case data collected as part of a COVID-19 dashboard collated via daily reports from the Malagasy authorities on reported cases of SARS-CoV-2 across the 22 regions of Madagascar. We compare the order of the timing of when cases were reported with predictions from a SARS-CoV-2 metapopulation model of Madagascar informed using various measures of connectivity including a gravity model based on different measures of distance, Internal Migration Flow data, and mobile phone data. Overall, the models based on mobile phone connectivity and the gravity-based on Euclidean distance best predicted the observed spread. The ranks of the regions most remote from the capital were more difficult to predict but interestingly, regions where the mobile phone connectivity model was more accurate differed from those where the gravity model was most accurate. This suggests that there may be additional features of mobility or connectivity that were consistently underestimated using all approaches but are epidemiologically relevant. This work highlights the importance of data availability and strengthening collaboration among different institutions with access to critical data - models are only as good as the data that they use, so building towards effective data-sharing pipelines is essential.

Existing human mobility data sources poorly predicted the spatial spread of SARS-CoV-2 in Madagascar.

For emerging epidemics such as the COVID-19 pandemic, quantifying travel is a key component of developing accurate predictive models of disease spread to inform public health planning. However, in many LMICs, traditional data sets on travel such as commuting surveys as well as non-traditional sources such as mobile phone data are lacking, or, where available, have only rarely been leveraged by the public health community. Evaluating the accuracy of available data to measure transmission-relevant travel may be further hampered by limited reporting of suspected and laboratory confirmed infections. Here, we leverage case data collected as part of a COVID-19 dashboard collated via daily reports from the Malagasy authorities on reported cases of SARS-CoV-2 across the 22 regions of Madagascar. We compare the order of the timing of when cases were reported with predictions from a SARS-CoV-2 metapopulation model of Madagascar informed using various measures of connectivity including a gravity model based on different measures of distance, Internal Migration Flow data, and mobile phone data. Overall, the models based on mobile phone connectivity and the gravity-based on Euclidean distance best predicted the observed spread. The ranks of the regions most remote from the capital were more difficult to predict but interestingly, regions where the mobile phone connectivity model was more accurate differed from those where the gravity model was most accurate. This suggests that there may be additional features of mobility or connectivity that were consistently underestimated using all approaches, but are epidemiologically relevant. This work highlights the importance of data availability and strengthening collaboration among different institutions with access to critical data - models are only as good as the data that they use, so building towards effective data-sharing pipelines is essential.

Cross-sectional cycle threshold values reflect epidemic dynamics of COVID-19 in Madagascar.

As the national reference laboratory for febrile illness in Madagascar, we processed samples from the first epidemic wave of COVID-19, between March and September 2020. We fit generalized additive models to cycle threshold (C t ) value data from our RT-qPCR platform, demonstrating a peak in high viral load, low-C t value infections temporally coincident with peak epidemic growth rates estimated in real time from publicly-reported incidence data and retrospectively from our own laboratory testing data across three administrative regions. We additionally demonstrate a statistically significant effect of duration of time since infection onset on C t value, suggesting that C t value can be used as a biomarker of the stage at which an individual is sampled in the course of an infection trajectory. As an extension, the population-level C t distribution at a given timepoint can be used to estimate population-level epidemiological dynamics. We illustrate this concept by adopting a recently-developed, nested modeling approach, embedding a within-host viral kinetics model within a population-level Susceptible-Exposed-Infectious-Recovered (SEIR) framework, to mechanistically estimate epidemic growth rates from cross-sectional C t distributions across three regions in Madagascar. We find that C t -derived epidemic growth estimates slightly precede those derived from incidence data across the first epidemic wave, suggesting delays in surveillance and case reporting. Our findings indicate that public reporting of C t values could offer an important resource for epidemiological inference in low surveillance settings, enabling forecasts of impending incidence peaks in regions with limited case reporting.

Variation in SARS-CoV-2 outbreaks across sub-Saharan Africa.

A surprising feature of the SARS-CoV-2 pandemic to date is the low burdens reported in sub-Saharan Africa (SSA) countries relative to other global regions. Potential explanations (for example, warmer environments1, younger populations2-4) have yet to be framed within a comprehensive analysis. We synthesized factors hypothesized to drive the pace and burden of this pandemic in SSA during the period from 25 February to 20 December 2020, encompassing demographic, comorbidity, climatic, healthcare capacity, intervention efforts and human mobility dimensions. Large diversity in the probable drivers indicates a need for caution in interpreting analyses that aggregate data across low- and middle-income settings. Our simulation shows that climatic variation between SSA population centers has little effect on early outbreak trajectories; however, heterogeneity in connectivity, although rarely considered, is likely an important contributor to variance in the pace of viral spread across SSA. Our synthesis points to the potential benefits of context-specific adaptation of surveillance systems during the ongoing pandemic. In particular, characterizing patterns of severity over age will be a priority in settings with high comorbidity burdens and poor access to care. Understanding the spatial extent of outbreaks warrants emphasis in settings where low connectivity could drive prolonged, asynchronous outbreaks resulting in extended stress to health systems.

Monitoring for outbreak-associated excess mortality in an African city: Detection limits in Antananarivo, Madagascar.

OBJECTIVES: Quantitative estimates of the impact of infectious disease outbreaks are required to develop measured policy responses. In many low- and middle-income countries, inadequate surveillance and incompleteness of death registration are important barriers. DESIGN: Here, we characterize how large an impact on mortality would have to be for being detectable using the uniquely detailed mortality notification data from the city of Antananarivo, Madagascar, with application to a recent measles outbreak. RESULTS: The weekly mortality rate of children during the 2018-2019 measles outbreak was 161% above the expected value at its peak, and the signal can be detected earlier in children than in the general population. This approach to detect anomalies from expected baseline mortality allows us to delineate the prevalence of COVID-19 at which excess mortality would be detectable with the existing death notification system in Antananarivo. CONCLUSIONS: Given current age-specific estimates of the COVID-19 fatality ratio and the age structure of the population in Antananarivo, we estimate that as few as 11 deaths per week in the 60-70 years age group (corresponding to an infection rate of approximately 1%) would detectably exceed the baseline. Data from 2020 will undergo necessary processing and quality control in the coming months. Our results provide a baseline for interpreting this information.

High variation expected in the pace and burden of SARS-CoV-2 outbreaks across sub-Saharan Africa.

A surprising feature of the SARS-CoV-2 pandemic to date is the low burdens reported in sub-Saharan Africa (SSA) countries relative to other global regions. Potential explanations (e.g., warmer environments1, younger populations2-4) have yet to be framed within a comprehensive analysis accounting for factors that may offset the effects of climate and demography. Here, we synthesize factors hypothesized to shape the pace of this pandemic and its burden as it moves across SSA, encompassing demographic, comorbidity, climatic, healthcare and intervention capacity, and human mobility dimensions of risk. We find large scale diversity in probable drivers, such that outcomes are likely to be highly variable among SSA countries. While simulation shows that extensive climatic variation among SSA population centers has little effect on early outbreak trajectories, heterogeneity in connectivity is likely to play a large role in shaping the pace of viral spread. The prolonged, asynchronous outbreaks expected in weakly connected settings may result in extended stress to health systems. In addition, the observed variability in comorbidities and access to care will likely modulate the severity of infection: We show that even small shifts in the infection fatality ratio towards younger ages, which are likely in high risk settings, can eliminate the protective effect of younger populations. We highlight countries with elevated risk of 'slow pace', high burden outbreaks. Empirical data on the spatial extent of outbreaks within SSA countries, their patterns in severity over age, and the relationship between epidemic pace and health system disruptions are urgently needed to guide efforts to mitigate the high burden scenarios explored here.

Morphometric signals of population decline in diademed sifakas occupying degraded rainforest habitat in Madagascar.

Anthropogenic habitat change can have varied impacts on primates, including both negative and positive outcomes. Even when behavioural shifts are seen, they may reflect decreased health, or simply behavioural flexibility; understanding this distinction is important for conservation efforts. This study examines habitat-related variation in adult and immature morphometrics among diademed sifakas (Propithecus diadema). We collected morphometric data from sifakas at Tsinjoarivo, Madagascar (19 years, 188 captures, 113 individuals). Captures spanned 12 groups, five within continuous forest ("CONT"), and seven in degraded fragments ("FRAG") where sifakas have lower nutritional intakes. Few consistent differences were found between CONT and FRAG groups. However, using home range quality as a covariate rather than a CONT/FRAG dichotomy revealed a threshold: the two FRAG groups in the lowest-quality habitat showed low adult mass and condition (wasting), and low immature mass and length (stunting). Though less-disturbed fragments apparently provide viable habitat, we suggest the sifakas in the most challenging habitats cannot evolve fast enough to keep up with such rapid habitat change. We suggest other long-lived organisms will show similar morphometric "warning signs" (wasting in adults, stunting in immatures); selected morphometric variables can thus be useful at gauging vulnerability of populations in the face of anthropogenic change.

Patterns of Exposure of Carnivores to Selected Pathogens in the Betampona Natural Reserve Landscape, Madagascar.

Carnivores of Madagascar are at increased risk of extinction due to anthropogenic loss of habitat, hunting, and interactions with introduced carnivores. Interactions between introduced and native animals also present the potential for introduction of pathogens into new geographic areas or host species. Here, we provide serologic data regarding pathogen exposure of domestic and native carnivores from the Betampona Natural Reserve Landscape, a protected area in eastern Madagascar. For the Eupleridae, we found limited evidence of exposure to viruses from domestic animals but greater prevalence for Toxoplasma gondii (39%) and Leptospira interrogans (40%). We also evaluated the associations between the presence of antibodies to selected pathogens and the demographic and spatial variables. We showed that individual characteristics such as sex and species were associated with exposure to T. gondii but not to L. interrogans or canine parvovirus (CPV). Finally, we investigated the spatial structure of pathogen exposure in Betampona and found no evidence of spatial structuring, indicating the absence of hotspots and agent-free refugia for T. gondii, L. interrogans, and CPV in the protected area. Our results may be useful for assessing and monitoring disease risk and for formulating control strategies to minimize the negative impact of exotic species on the endemic carnivores of Madagascar.

Interactions Between Carnivores in Madagascar and the Risk of Disease Transmission.

Introduced carnivores exert considerable pressure on native predators through predation, competition and disease transmission. Recent research shows that exotic carnivores negatively affect the distribution and abundance of the native and endangered carnivores of Madagascar. In this study, we provide information about the frequency and distribution of interactions between exotic (dogs and cats) and native carnivores (Eupleridae) in the Betampona Natural Reserve (BNR), Madagascar, using noninvasive camera trap surveys. Domestic dogs (Canis familiaris) were the most frequently detected carnivore species within the BNR, and we found that indirect interactions between exotic and native carnivores were frequent (n = 236). Indirect interactions were more likely to occur near the research station (incidence rate ratio = 0.91), which may constitute a disease transmission hot spot for carnivores at BNR. The intervals between capture of native and exotic carnivores suggest that there is potential for pathogen transmission between species in BNR. These capture intervals were significantly shorter near the edge of the reserve (P = 0.04). These data could be used to implement biosecurity measures to monitor interactions and prevent disease transmission between species at the domestic animal and wildlife interface.

PREVALENCE OF ANTIBODIES TO SELECTED VIRUSES AND PARASITES IN INTRODUCED AND ENDEMIC CARNIVORES IN WESTERN MADAGASCAR.

Introduced animals impact endemic populations through predation, competition, and disease transmission. Populations of endemic carnivores in Madagascar are declining, and pathogens transmitted from introduced species may further endanger these unique species. We assessed the exposure of introduced and endemic carnivores to common viral and parasitic pathogens in two national parks of Madagascar (Kirindy Mitea National Park and Ankarafantsika National Park) and their neighboring villages. We also identified variables associated with the presence of antibodies to these pathogens in fosa ( Cryptoprocta ferox ). Introduced and endemic species were exposed to canine parvovirus, canine herpesvirus, feline calicivirus, and Toxoplasma gondii . Domestic dogs ( Canis familiaris ) and cats ( Felis catus ) may be sources of infection for these pathogens. Prevalence of antibodies to Toxoplasma in captured fosa was >93%, and adults were more likely to be exposed than immature individuals. Our data provide a basis upon which to evaluate and manage risks of pathogen transmission between species.

GASTROINTESTINAL PARASITES OF CAPTIVE AND FREE-LIVING LEMURS AND DOMESTIC CARNIVORES IN EASTERN MADAGASCAR.

Fecal samples from captive and free-living lemurs at Ivoloina Zoological Park (IZP) and domestic carnivores from six villages surrounding IZP were evaluated between July and August 2012. Free-living lemurs from Betampona Natural Reserve (BNR), a relatively pristine rainforest fragment 40 km away, were also evaluated in November 2013. All 33 dogs sampled (100%) and 16 of 22 cats sampled (72.7%) were parasitized, predominantly with nematodes (strongyles, ascarids, and spirurids) as well as cestodes and protozoans. Similar types of parasites were identified in the lemur populations. Identification of spirurid nematodes and protozoans in the lemur fecal samples were of concern due to previously documented morbidity and mortality in lemurs from these parasitic agents. Twelve of 13 free-living (93%) and 31 of 49 captive (63%) lemurs sampled at IZP had a higher parasite prevalence than lemurs at BNR, with 13 of 24 (54%) being parasitized. The lemurs in BNR are likely at risk of increased exposure to these parasites and, therefore, increased morbidity and mortality, as humans and their domestic animals are encroaching on this natural area.

Pathogenic enterobacteria in lemurs associated with anthropogenic disturbance.

As human population density continues to increase exponentially, speeding the reduction and fragmentation of primate habitat, greater human-primate contact is inevitable, making higher rates of pathogen transmission likely. Anthropogenic effects are particularly evident in Madagascar, where a diversity of endemic lemur species are threatened by rapid habitat loss. Despite these risks, knowledge of how anthropogenic activities affect lemur exposure to pathogens is limited. To improve our understanding of this interplay, we non-invasively examined six species of wild lemurs in Ranomafana National Park for enteric bacterial pathogens commonly associated with diarrheal disease in human populations in Madagascar. Patterns of infection with Enterotoxigenic Escherichia coli, Shigella spp., Salmonella enterica, Vibrio cholerae, and Yersinia spp. (enterocolitica and pseudotuberculosis) were compared between lemurs inhabiting intact forest and lemurs inhabiting degraded habitat with frequent exposure to tourism and other human activity. Fecal samples acquired from humans, livestock, and rodents living near the degraded habitat were also screened for these bacteria. Remarkably, only lemurs living in disturbed areas of the park tested positive for these pathogens. Moreover, all of these pathogens were present in the human, livestock, and/or rodent populations. These data suggest that lemurs residing in forests altered or frequented by people, livestock, or peridomestic rodents, are at risk for infection by these diarrhea-causing enterobacteria and other similarly transmitted pathogens.

Complex epidemiology and zoonotic potential for Cryptosporidium suis in rural Madagascar.

Cryptosporidium spp. is the most important parasitic diarrheal agent in the world, is among the top four causes of moderate-to-severe diarrheal disease in young children in developing nations, and is problematic as an opportunistic co-infection with HIV. In addition, Cryptosporidium is a persistent challenge for livestock production. Despite its zoonotic potential, few studies have examined the ecology and epidemiology of this pathogen in rural systems characterized by high rates of overlap among humans, domesticated animals, and wildlife. To improve our understanding of the zoonotic potential of Cryptosporidium species in the rural tropics, we screened humans, livestock, peridomestic rodents, and wildlife using PCR-RFLP and sequencing-based approaches to distinguish species of Cryptosporidium in rural southeastern Madagascar. Cryptosporidium of multiple species/genotypes were apparent in this study system. Interestingly, C. suis was the dominant species of Cryptosporidium in the region, infecting humans (n=1), cattle (n=18), pigs (n=3), and rodents (n=1). The broad species range of C. suis and the lack of common cattle Cryptosporidium species (Cryptosporidium parvum and Cryptosporidium andersoni) in this system are unique. This report represents the fifth confirmed case of C. suis infection in humans, and the first case in Africa. Few rural human and livestock populations have been screened for Cryptosporidium using genus-specific genotyping methods. Consequently, C. suis may be more widespread in human and cattle populations than previously believed.

Biomedical evaluation of Verreaux's sifaka (Propithecus verreauxi) from Kirindy Mitea National Park in Madagascar.

Evaluation of the health, prevalence, and incidence of diseases in wild populations is a critical component of wildlife management. In addition, the establishment of reference physiologic parameters can Verreaux's sifaka (Propithecus verreauxi) from Kirindy Mitea National Park, Madagascar, during two field captures incontribute to the assessment of population risks. Complete medical evaluations were performed on 33 wild June 2010 and June 2011. Each animal received a complete physical examination: weight, body temperature, heart rate, and respiratory rate were recorded, and ectoparasites collected. Blood samples were collected for complete blood cell count, differential white blood cell count, hemoparasite examination, serum biochemical profile, fat-soluble vitamin analysis, trace mineral analysis, and toxoplasmosis and viral serology. Fecal samples were collected for bacterial culture and endoparasite examination. Significant differences exist between age classes for neutrophil and lymphocyte count, alkaline phosphatase, and creatinine values. Parasites detected were Callistoura sp., Bertiella lemuriformis, and Dipetalonema petteri. This publication reports the first complete biomedical evaluation of the P. verreauxi and provides a basis for hematologic and biochemical comparisons of P. verreauxi in the wild.