Rift Valley fever (RVF) is a vector-borne viral disease widespread in Africa. The primary cycle involves mosquitoes and wild and domestic ruminant hosts. Humans are usually contaminated after contact with infected ruminants. As many environmental, agricultural, epidemiological, and anthropogenic factors are implicated in RVF spread, the multidisciplinary One Health approach was needed to identify the drivers of RVF epidemics in Madagascar. We examined the environmental patterns associated with these epidemics, comparing human and ruminant serological data with environmental and cattle-trade data. In contrast to East Africa, environmental drivers did not trigger the epidemics: They only modulated local Rift Valley fever virus (RVFV) transmission in ruminants. Instead, RVFV was introduced through ruminant trade and subsequent movement of cattle between trade hubs caused its long-distance spread within the country. Contact with cattle brought in from infected districts was associated with higher infection risk in slaughterhouse workers. The finding that anthropogenic rather than environmental factors are the main drivers of RVF infection in humans can be used to design better prevention and early detection in the case of RVF resurgence in the region.vector-borne infection | zoonosis | El Niño | cattle trade | One Health

Rift Valley fever virus (RVFV) is an arthropod-borne phlebovirus reported to be circulating in most parts of Africa. Since 2009, RVFV has been suspected of continuously circulating in the Union of Comoros. To estimate the incidence of RVFV antibody acquisition in the Comorian ruminant population, 191 young goats and cattle were selected in six distinct zones and sampled periodically from April 2010 to August 2011. We found an estimated incidence of RVFV antibody acquisition of 17.5% (95% confidence interval (CI): [8.9–26.1]) with a significant difference between islands (8.2% in Grande Comore, 72.3% in Moheli and 5.8% in Anjouan). Simultaneously, a longitudinal entomological survey was conducted and ruminant trade-related information was collected. No RVFV RNA was detected out of the 1,568 blood-sucking caught insects, including three potential vectors of RVFV mosquito species. Our trade survey suggests that there is a continuous flow of live animals from eastern Africa to the Union of Comoros and movements of ruminants between the three Comoro islands. Finally, a cross-sectional study was performed in August 2011 at the end of the follow-up. We found an estimated RVFV antibody prevalence of 19.3% (95% CI: [15.6%–23.0%]). Our findings suggest a complex RVFV epidemiological cycle in the Union of Comoros with probable inter-islands differences in RVFV circulation patterns. Moheli, and potentially Anjouan, appear to be acting as endemic reservoir of infection whereas RVFV persistence in Grande Comore could be correlated with trade in live animals with the eastern coast of Africa. More data are needed to estimate the real impact of the disease on human health and on the national economy.

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Q fever is a widespread zoonosis that is caused by Coxiella burnetii (C. burnetii), and ruminants are identified as the main sources of human infections. Some human cases have been described, but very limited information was available about Q fever in ruminants on Reunion Island, a tropical island in the Indian Ocean. A cross-sectional study was undertaken from March 2011 to August 2012 to assess the Q fever prevalence and to identify the major risk factors of C. burnetii infection in ruminants. A total of 516 ruminants (245 cattle, 137 sheep and 134 goats) belonging to 71 farms and localized in different ecosystems of the island were randomly selected. Samples of blood, vaginal mucus and milk were concomitantly collected from females, and a questionnaire was submitted to the farmers. Ticks from positively detected farms were also collected. The overall seropositivity was 11.8% in cattle, 1.4% in sheep and 13.4% in goats. C. burnetii DNA was detected by PCR in 0.81%, 4.4% and 20.1% in cow, sheep and goat vaginal swabs, respectively. C. burnetii shedding in milk was observed in 1% of cows, 0% in sheep and 4.7% in goats. None of the ticks were detected to be positive for C. burnetii. C. burnetii infection increased when the farm was exposed to prevailing winds and when there were no specific precautions for a visitor before entering the farm, and they decreased when a proper quarantine was set up for any introduction of a new ruminant and when the animals returned to the farm at night. MLVA genotyping confirmed the role of these risk factors in infection.

Toxoplasma gondii is a protozoan parasite infecting humans and animals. Wild boars Sus scrofa are a potential source of human infection and an appropriate biological model for analyzing T. gondii dynamics in the environment. Here, we aimed to identify environmental factors explaining the seroprevalence of toxoplasmosis in French wild boar populations. Considering 938 individuals sampled from 377 'communes', overall seroprevalence was 23% (95% confidence interval: [22-24]). Using a Poisson regression, we found that the number of seropositive wild boars detected per 'commune' was positively associated with the presence of European wildcats (Felis silvestris) and moderate winter temperatures.

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The purpose of the study was to weigh the community burden of chikungunya determinants on Reunion island. Risk factors were investigated within a subset of 2101 adult persons from a population-based cross-sectional serosurvey, using Poisson regression models for dichotomous outcomes. Design-based risk ratios and population attributable fractions (PAF) were generated distinguishing individual and contextual (i.e. that affect individuals collectively) determinants. The disease burden attributable to contextual determinants was twice that of individual determinants (overall PAF value 89.5% vs. 44.1%). In a model regrouping both categories of determinants, the independent risk factors were by decreasing PAF values: an interaction term between the reporting of a chikungunya history in the neighbourhood and individual house (PAF 45.9%), a maximal temperature of the month preceding the infection higher than 28.5 °C (PAF 25.7%), a socio-economically disadvantaged neighbourhood (PAF 19.0%), altitude of dwelling (PAF 13.1%), cumulated rainfalls of the month preceding the infection higher than 65 mm (PAF 12.6%), occupational inactivity (PAF 11.6%), poor knowledge on chikungunya transmission (PAF 7.3%) and obesity/overweight (PAF 5.2%). Taken together, these covariates and their underlying causative factors uncovered 80.8% of chikungunya at population level. Our findings lend support to a major role of contextual risk factors in chikungunya virus outbreaks.

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