Prediction of a Rift Valley fever outbreak

The Role of Temperature in Transmission of Zoonotic Arboviruses

We reviewed the literature on the role of temperature in transmission of zoonotic arboviruses. Vector competence is affected by both direct and indirect effects of temperature, and generally increases with increasing temperature, but results may vary by vector species, population, and viral strain. Temperature additionally has a significant influence on life history traits of vectors at both immature and adult life stages, and for important behaviors such as blood-feeding and mating. Similar to vector competence, temperature effects on life history traits can vary by species and population. Vector, host, and viral distributions are all affected by temperature, and are generally expected to change with increased temperatures predicted under climate change. Arboviruses are generally expected to shift poleward and to higher elevations under climate change, yet significant variability on fine geographic scales is likely. Temperature effects are generally unimodal, with increases in abundance up to an optimum, and then decreases at high temperatures. Improved vector distribution information could facilitate future distribution modeling. A wide variety of approaches have been used to model viral distributions, although most research has focused on the West Nile virus. Direct temperature effects are frequently observed, as are indirect effects, such as through droughts, where temperature interacts with rainfall. Thermal biology approaches hold much promise for syntheses across viruses, vectors, and hosts, yet future studies must consider the specificity of interactions and the dynamic nature of evolving biological systems.

Unexplored Opportunities: Use of Climate- and Weather-Driven Early Warning Systems to Reduce the Burden of Infectious Diseases

PURPOSE OF REVIEW

Weather and climate influence multiple aspects of infectious disease ecology. Creating and applying early warning systems based on temperature, precipitation, and other environmental data can identify where and when outbreaks of climate-sensitive infectious diseases could occur and can be used by decision makers to allocate resources. Whether an outbreak actually occurs depends heavily on other social, political, and institutional factors.

RECENT FINDINGS

Improving the timing and confidence of seasonal climate forecasting, coupled with knowledge of exposure-response relationships, can identify prior conditions conducive to disease outbreaks weeks to months in advance of outbreaks. This information could then be used by public health professionals to improve surveillance in the most likely areas for threats. Early warning systems are well established for drought and famine. And while weather- and climate-driven early warning systems for certain diseases, such as dengue fever and cholera, are employed in some regions, this area of research is underdeveloped. Early warning systems based on temperature, precipitation, and other environmental data provide an opportunity for early detection leading to early action and response to potential pathogen threats, thereby reducing the burden of disease when compared with passive health indicator-based surveillance systems.

A comparative genome analysis of Rift Valley Fever virus isolates from foci of the disease outbreak in South Africa in 2008-2010

Rift Valley fever (RVF) is a re-emerging zoonotic disease responsible for major losses in livestock production, with negative impact on the livelihoods of both commercial and resource-poor farmers in sub-Sahara African countries. The disease remains a threat in countries where its mosquito vector thrives. Outbreaks of RVF usually follow weather conditions which favour increase in mosquito populations. Such outbreaks are usually cyclical, occurring every 10–15 years. Recent outbreaks of the disease in South Africa have occurred unpredictably and with increased frequency. In 2008, outbreaks were reported in Mpumalanga, Limpopo and Gauteng provinces, followed by 2009 outbreaks in KwaZulu-Natal, Mpumalanga and Northern Cape provinces and in 2010 in the Eastern Cape, Northern Cape, Western Cape, North West, Free State and Mpumalanga provinces. By August 2010, 232 confirmed infections had been reported in humans, with 26 confirmed deaths.To investigate the evolutionary dynamics of RVF viruses (RVFVs) circulating in South Africa, we undertook complete genome sequence analysis of isolates from animals at discrete foci of the 2008–2010 outbreaks. The genome sequences of these viruses were compared with those of the viruses from earlier outbreaks in South Africa and in other countries. The data indicate that one 2009 and all the 2008 isolates from South Africa and Madagascar (M49/08) cluster in Lineage C or Kenya-1. The remaining of the 2009 and 2010 isolates cluster within Lineage H, except isolate M259_RSA_09, which is a probable segment M reassortant. This information will be useful to agencies involved in the control and management of Rift Valley fever in South Africa and the neighbouring countries.

A single RVF virus serotype exists, yet differences in virulence and pathogenicity of the virus have been observed. This necessitates the need for detailed genetic characterization of various isolates of the virus. Some of the RVF virus isolates that caused the 2008–2010 disease outbreaks in South Africa were most probably reassortants resulting from exchange of portions of the genome, particularly those of segment M. Although clear association between RVFV genotype and phenotype has not been established, various amino acid substitutions have been implicated in the phenotype. Viruses with amino acid substitutions from glycine to glutamic acid at position 277 of segment M have been shown to be more virulent in mice in comparison to viruses with glycine at the same position. Phylogenetic analysis carried out in this study indicated that the viruses responsible for the 2008–2010 RVF outbreaks in South Africa were not introduced from outside the country, but mutated over time and caused the outbreaks when environmental conditions became favourable.

Individual-based network model for Rift Valley fever in Kabale District, Uganda

Rift Valley fever (RVF) is a zoonotic disease, that causes significant morbidity and mortality among ungulate livestock and humans in endemic regions. In East Africa, the causative agent of the disease is Rift Valley fever virus (RVFV) which is primarily transmitted by multiple mosquito species in Aedes and Mansonia genera during both epizootic and enzootic periods in a complex transmission cycle largely driven by environmental and climatic factors. However, recent RVFV activity in Uganda demonstrated the capability of the virus to spread into new regions through livestock movements, and underscored the need to develop effective mitigation strategies to reduce transmission and prevent spread among cattle populations. We simulated RVFV transmission among cows in 22 different locations of the Kabale District in Uganda using real world livestock data in a network-based model. This model considered livestock as a spatially explicit factor in different locations subjected to specific vector and environmental factors, and was configured to investigate and quantitatively evaluate the relative impacts of mosquito control, livestock movement, and diversity in cattle populations on the spread of the RVF epizootic. We concluded that cattle movement should be restricted for periods of high mosquito abundance to control epizootic spreading among locations during an RVF outbreak. Importantly, simulation results also showed that cattle populations with heterogeneous genetic diversity as crossbreeds were less susceptible to infection compared to homogenous cattle populations.

Global Disease Outbreaks Associated with the 2015-2016 El Niño Event

Interannual climate variability patterns associated with the El Niño-Southern Oscillation phenomenon result in climate and environmental anomaly conditions in specific regions worldwide that directly favor outbreaks and/or amplification of variety of diseases of public health concern including chikungunya, hantavirus, Rift Valley fever, cholera, plague, and Zika. We analyzed patterns of some disease outbreaks during the strong 2015–2016 El Niño event in relation to climate anomalies derived from satellite measurements. Disease outbreaks in multiple El Niño-connected regions worldwide (including Southeast Asia, Tanzania, western US, and Brazil) followed shifts in rainfall, temperature, and vegetation in which both drought and flooding occurred in excess (14–81% precipitation departures from normal). These shifts favored ecological conditions appropriate for pathogens and their vectors to emerge and propagate clusters of diseases activity in these regions. Our analysis indicates that intensity of disease activity in some ENSO-teleconnected regions were approximately 2.5–28% higher during years with El Niño events than those without. Plague in Colorado and New Mexico as well as cholera in Tanzania were significantly associated with above normal rainfall (p < 0.05); while dengue in Brazil and southeast Asia were significantly associated with above normal land surface temperature (p < 0.05). Routine and ongoing global satellite monitoring of key climate variable anomalies calibrated to specific regions could identify regions at risk for emergence and propagation of disease vectors. Such information can provide sufficient lead-time for outbreak prevention and potentially reduce the burden and spread of ecologically coupled diseases.

Rift Valley fever: An open-source transmission dynamics simulation model

Rift Valley fever (RVF) is one of the major viral zoonoses in Africa, affecting humans and several domestic animal species. The epidemics in eastern Africa occur in a 5-15 year cycle coinciding with abnormally high rainfall generally associated to the warm phase of the El Niño event. However, recently, evidence has been gathered of inter-epidemic transmission. An open-source, easily applicable, accessible and modifiable model was built to simulate the transmission dynamics of RVF. The model was calibrated using data collected in the Kilombero Valley in Tanzania with people and cattle as host species and Ædes mcintoshi, Æ. ægypti and two Culex species as vectors. Simulations were run over a period of 27 years using standard parameter values derived from two previous studies in this region. Our model predicts low-level transmission of RVF, which is in line with epidemiological studies in this area. Emphasis in our simulation was put on both the dynamics and composition of vector populations in three ecological zones, in order to elucidate the respective roles played by different vector species: the model output did indicate the necessity of Culex involvement and also indicated that vertical transmission in Ædes mcintoshi may be underestimated. This model, being built with open-source software and with an easy-to-use interface, can be adapted by researchers and control program managers to their specific needs by plugging in new parameters relevant to their situation and locality.

Data and tools to integrate climate and environmental information into public health

BACKGROUND

During the last 30 years, the development of geographical information systems and satellites for Earth observation has made important progress in the monitoring of the weather, climate, environmental and anthropogenic factors that influence the reduction or the reemergence of vector-borne diseases. Analyses resulting from the combination of geographical information systems (GIS) and remote sensing have improved knowledge of climatic, environmental, and biodiversity factors influencing vector-borne diseases (VBDs) such as malaria, visceral leishmaniasis, dengue, Rift Valley fever, schistosomiasis, Chagas disease and leptospirosis. These knowledge and products developed using remotely sensed data helped and continue to help decision makers to better allocate limited resources in the fight against VBDs.

MAIN BODY

Because VBDs are linked to climate and environment, we present here our experience during the last four years working with the projects under the, World Health Organization (WHO)/ The Special Programme for Research and Training in Tropical Diseases (TDR)-International Development Research Centre (IDRC) Research Initiative on VBDs and Climate Change to integrate climate and environmental information into research and decision-making processes. The following sections present the methodology we have developed, which uses remote sensing to monitor climate variability, environmental conditions, and their impacts on the dynamics of infectious diseases. We then show how remotely sensed data can be accessed and evaluated and how they can be integrated into research and decision-making processes for mapping risks, and creating Early Warning Systems, using two examples from the WHO TDR projects based on schistosomiasis analysis in South Africa and Trypanosomiasis in Tanzania.

CONCLUSIONS

The tools presented in this article have been successfully used by the projects under the WHO/TDR-IDRC Research Initiative on VBDs and Climate Change. Combined with capacity building, they are an important piece of work which can significantly contribute to the goals of WHO Global Vector Control Response and to the Sustainable Development Goals especially those on health and climate action.

Participatory survey of Rift Valley fever in nomadic pastoral communities of North-central Nigeria: The associated risk pathways and factors

BACKGROUND

Rift Valley fever (RVF) is an emerging neglected mosquito-borne viral zoonotic disease of domestic animals and humans, with potential for global expansion. The objectives of this study were: to assess perceived relative burden and seasonality of RVF in nomadic cattle herds and validate the burden with sero-prevalence impact; and assess perceived risk factors associated with the disease and risk pathways for RVF virus in nomadic pastoral herds of North-central Nigeria using pastoralists' existing veterinary knowledge.

METHODS

Participatory Epidemiology (PE) survey was conducted in Fulani nomadic pastoral communities domiciled in Niger State between January and December 2015. A cross-sectional sero-prevalence investigation was also carried out in nomadic pastoral cattle herds to validate outcomes of PE. A total of nine nomadic pastoral communities were purposively selected for qualitative impact assessment using Participatory Rural Appraisal tools, while 97 cattle randomly sampled from 15 purposively selected nomadic herds and had their sera analyzed using c-ELISA. Kendall's Coefficient of Concordance W statistics and OpenEpi 2.3.1 were used for statistical analyses.

RESULTS

Mean proportional piles (relative burden) of RVF (Gabi-gabiF) was 8.3%, and nomads agreement on the burden was strong (W = 0.6855) and statistically significant (P<0.001). This was validated by 11.3% (11/97; 95% CI: 6.1-18.9) sero-positivity (quantitative impact). Mean matrix scores of prominent clinical signs associated with RVF were fever (3.1), anorexia (2.1), abortion (4.1), nasal discharge (3.3), neurological disorder (8.4), diarrhoea (3.2), and sudden death (4.4), with strong agreement (W = 0.6687) and statistically significant (p<0.001). Mean proportional piles of pastoralists' perceived risk factors identified to influenced RVF occurrence were: availability of mosquitoes (18 piles, 17.6%), high cattle density (16 piles, 15.9%) and high rainfall (12 piles, 12.2%). Agreement on the risk factors was strong (W = 0.8372) and statistically significant (p<0.01). Mean matrix scores for the Entry pathway of RVF virus into the nomadic pastoral herds were: presence of RVFV infected mosquitoes (tiny biting flies) (7.9), presence of infected cattle in herds (8.4), and contacts of herd with infected wild animals at grazing (10.1). Mean matrix scores for the Spread pathway of RVF virus in herds were bites of infected mosquitoes (5.1), contacts with infected aborted fetuses/fluids (7.8), and contaminated pasture with aborted fetuses/fluids (9.7). Agreement on risk pathways was strong (W = 0.6922) and statistically significant (p<0.03). Key informants scored RVF to occurred more in Damina or late rainy season (5.3), followed by Kaka or early dry season (3.3), with strong agreement (W = 0.8719) and statistically significant (P<0.01). This study highlighted the significant existing knowledge level about RVF contained in nomadic pastoralists.

CONCLUSIONS

The use of PE approach is needful in active surveillance of livestock diseases in pastoral communities domiciled in highly remote areas. RVF surveillance system, control and prevention programmes that take the identified risk factors and pathways into consideration will be beneficial to the livestock industry in Nigeria, and indeed Africa. An 'OneHealth' approach is needed to improve efficiency of RVF research, surveillance, prevention and control systems, so as to assure food security and public health in developing countries.

Seroprevalence of Rift Valley fever virus in cattle in the Democratic Republic of the Congo

This study aimed at assessing the serological and virological status of Rift Valley fever virus (RVFV) in cattle from four climatically diverse zones of the Democratic Republic of the Congo (DRC). A total of 1675 sera samples collected between 2014 and 2015 from cattle without clinical manifestation of RVF infection were tested using competitive and capture enzyme ELISA to detect both IgG and IgM. RT-PCR was used for the detection of nucleic acid of RVFV. Out of the 1675 cattle sera tested, 203 were found to be IgG-positive, giving an overall true seroprevalence of 12.37% (95% CI 10.86-14.05). This seroprevalence varied between the four zones with a seroprevalence of 16.16% (95% CI 12.86-20.12), 14.70% (95% CI 11.72-18.29), 10.82% (95% CI 7.19-14.19), and 7.34% (95% CI 5.13-10.41) recorded in cattle sampled in the mountainous, humid savannah, dry savannah, and forest zones, respectively (p < 0.05, χ² = 17.26). A higher true seroprevalence of 14.58% (95% CI 9.3-22.13) was found in animals aged 1 year compared to 10.43% (95% CI 8.12-13.30) and 13.16% (95% CI 11.19-15.42) in groups aged between 2-3 and > 3 years, respectively, although the difference was not statistically significant (p > 0.05, χ² = 2.95). Similarly, no statistically significant difference (p > 0.05, χ² = 0.04) was found between the sexes of the animals. Among the IgG-positive samples screened for anti-RVFV IgM, only 1.47% (3/203) was IgM-positive. One of the IgM-positive samples was positive by RT-PCR. These findings reveal country-wide distribution of RVF in the DRC for the first time.

Environmental limits of Rift Valley fever revealed using ecoepidemiological mechanistic models

Vector-borne diseases (VBDs) of humans and domestic animals are a significant component of the global burden of disease and a key driver of poverty. The transmission cycles of VBDs are often strongly mediated by the ecological requirements of the vectors, resulting in complex transmission dynamics, including intermittent epidemics and an unclear link between environmental conditions and disease persistence. An important broader concern is the extent to which theoretical models are reliable at forecasting VBDs; infection dynamics can be complex, and the resulting systems are highly unstable. Here, we examine these problems in detail using a case study of Rift Valley fever (RVF), a high-burden disease endemic to Africa. We develop an ecoepidemiological, compartmental, mathematical model coupled to the dynamics of ambient temperature and water availability and apply it to a realistic setting using empirical environmental data from Kenya. Importantly, we identify the range of seasonally varying ambient temperatures and water-body availability that leads to either the extinction of mosquito populations and/or RVF (nonpersistent regimens) or the establishment of long-term mosquito populations and consequently, the endemicity of the RVF infection (persistent regimens). Instabilities arise when the range of the environmental variables overlaps with the threshold of persistence. The model captures the intermittent nature of RVF occurrence, which is explained as low-level circulation under the threshold of detection, with intermittent emergence sometimes after long periods. Using the approach developed here opens up the ability to improve predictions of the emergence and behaviors of epidemics of many other important VBDs.

Systematic literature review of Rift Valley fever virus seroprevalence in livestock, wildlife and humans in Africa from 1968 to 2016

Background

Rift Valley fever virus (RVFV) is a zoonotic arbovirus that causes severe disease in livestock and humans. The virus has caused recurrent outbreaks in Africa and the Arabian Peninsula since its discovery in 1931. This review sought to evaluate RVFV seroprevalence across the African continent in livestock, wildlife and humans in order to understand the spatio-temporal distribution of RVFV seroprevalence and to identify knowledge gaps and areas requiring further research. Risk factors associated with seropositivity were identified and study designs evaluated to understand the validity of their results.

Methodology

The Preferred Reporting of Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used to produce a protocol to systematically search for RVFV seroprevalence studies in PubMed and Web of Science databases. The Strengthening the Reporting of Observational studies in Epidemiology (STROBE) statement guided the evaluation of study design and analyses.

Principal findings

A total of 174 RVFV seroprevalence studies in 126 articles fulfilled the inclusion criteria. RVFV seroprevalence was recorded in 31 African countries from 1968 to 2016 and varied by time, species and country. RVFV seroprevalence articles including either livestock and humans or livestock and wildlife seroprevalence records were limited in number (8/126). No articles considered wildlife, livestock and human seroprevalence concurrently, nor wildlife and humans alone. Many studies did not account for study design bias or the sensitivity and specificity of diagnostic tests.

Conclusions

Future research should focus on conducting seroprevalence studies at the wildlife, livestock and human interface to better understand the nature of cross-species transmission of RVFV. Reporting should be more transparent and biases accounted for in future seroprevalence research to understand the true burden of disease on the African continent.

Rift Valley fever virus (RVFV) is a vector-borne virus that infects wildlife and livestock, and can subsequently spread to humans. Due to the nature of the disease it has the potential to cause substantial economic and public health impacts. Rift Valley Fever (RVF) has been identified in Africa and the Arabian Peninsula, but has the potential to spread more widely. This systematic review assessed the distribution of RVF in livestock and humans in Africa by collating all the relevant studies we could find, extracting the data and critically evaluating them. Understanding when and where RVF has occurred in Africa and why some animals and humans get disease helps target control strategies and, in particular, those that reduce spread from livestock to humans. Furthermore, by evaluating past studies we can ensure that future ones are more robust and reproducible, so they can help us better understand the disease.

Early warning and response system (EWARS) for dengue outbreaks: Recent advancements towards widespread applications in critical settings

Background

Dengue outbreaks are increasing in frequency over space and time, affecting people’s health and burdening resource-constrained health systems. The ability to detect early emerging outbreaks is key to mounting an effective response. The early warning and response system (EWARS) is a toolkit that provides countries with early-warning systems for efficient and cost-effective local responses. EWARS uses outbreak and alarm indicators to derive prediction models that can be used prospectively to predict a forthcoming dengue outbreak at district level.

Methods

We report on the development of the EWARS tool, based on users’ recommendations into a convenient, user-friendly and reliable software aided by a user’s workbook and its field testing in 30 health districts in Brazil, Malaysia and Mexico.

Findings

34 Health officers from the 30 study districts who had used the original EWARS for 7 to 10 months responded to a questionnaire with mainly open-ended questions. Qualitative content analysis showed that participants were generally satisfied with the tool but preferred open-access vs. commercial software. EWARS users also stated that the geographical unit should be the district, while access to meteorological information should be improved. These recommendations were incorporated into the second-generation EWARS-R, using the free R software, combined with recent surveillance data and resulted in higher sensitivities and positive predictive values of alarm signals compared to the first-generation EWARS. Currently the use of satellite data for meteorological information is being tested and a dashboard is being developed to increase user-friendliness of the tool. The inclusion of other Aedes borne viral diseases is under discussion.

Conclusion

EWARS is a pragmatic and useful tool for detecting imminent dengue outbreaks to trigger early response activities.

Rift Valley Fever in Egypt and other African countries: Historical review, recent outbreaks and possibility of disease occurrence in Egypt

This article reviews and discusses the historical and recent status of Rift Valley Fever (RVF) in Egypt and the other African countries based on the available and scattered reports. The recent outbreaks in African countries were reviewed and mapped out. Four major epidemics have been recorded in Egypt (1977, 1978, 1993 and 2003). The outbreak resulted in unpredicted human disease with severe clinical manifestations and heavy mortality as well as many abortions and deaths in sheep, goats, cattle, water buffalo and camels. Of the 18 culicine mosquito species that occur in Egypt, Culex pipiens and Cx. antennatus were implicated as vectors of RVF in Egypt based on their natural infection with RVF virus. Aedes caspius was also suspected of disseminating the virus among livestock based on host feeding and vector competence studies. The epidemiological factors related to the introduction and spread of RVF in Egypt are discussed. The study concluded that due to the availability and abundance of the potential vectors, suitability of environmental conditions, continuous importation of livestock's from Sudan, and the close association of susceptible domestic animals with humans, the RVF virus could possibly occur and circulate in Egypt.

Ecological niche modeling of Aedes mosquito vectors of chikungunya virus in southeastern Senegal

Background

Chikungunya virus (CHIKV) originated in a sylvatic cycle of transmission between non-human animal hosts and vector mosquitoes in the forests of Africa. Subsequently the virus jumped out of this ancestral cycle into a human-endemic transmission cycle vectored by anthropophilic mosquitoes. Sylvatic CHIKV cycles persist in Africa and continue to spill over into humans, creating the potential for new CHIKV strains to enter human-endemic transmission. To mitigate such spillover, it is first necessary to delineate the distributions of the sylvatic mosquito vectors of CHIKV, to identify the environmental factors that shape these distributions, and to determine the association of mosquito presence with key drivers of virus spillover, including mosquito and CHIKV abundance. We therefore modeled the distribution of seven CHIKV mosquito vectors over two sequential rainy seasons in Kédougou, Senegal using Maxent.

Methods

Mosquito data were collected in fifty sites distributed in five land cover classes across the study area. Environmental data representing land cover, topographic, and climatic factors were included in the models. Models were compared and evaluated using area under the receiver operating characteristic curve (AUROC) statistics. The correlation of model outputs with abundance of individual mosquito species as well as CHIKV-positive mosquito pools was tested.

Results

Fourteen models were produced and evaluated; the environmental variables most strongly associated with mosquito distributions were distance to large patches of forest, landscape patch size, rainfall, and the normalized difference vegetation index (NDVI). Seven models were positively correlated with mosquito abundance and one (Aedes taylori) was consistently, positively correlated with CHIKV-positive mosquito pools. Eight models predicted high relative occurrence rates of mosquitoes near the villages of Tenkoto and Ngary, the areas with the highest frequency of CHIKV-positive mosquito pools.

Conclusions

Of the environmental factors considered here, landscape fragmentation and configuration had the strongest influence on mosquito distributions. Of the mosquito species modeled, the distribution of Ae. taylori correlated most strongly with abundance of CHIKV, suggesting that presence of this species will be a useful predictor of sylvatic CHIKV presence.

Electronic supplementary material

The online version of this article (10.1186/s13071-018-2832-6) contains supplementary material, which is available to authorized users.

Local disease-ecosystem-livelihood dynamics: reflections from comparative case studies in Africa

This article explores the implications for human health of local interactions between disease, ecosystems and livelihoods. Five interdisciplinary case studies addressed zoonotic diseases in African settings: Rift Valley fever (RVF) in Kenya, human African trypanosomiasis in Zambia and Zimbabwe, Lassa fever in Sierra Leone and henipaviruses in Ghana. Each explored how ecological changes and human–ecosystem interactions affect pathogen dynamics and hence the likelihood of zoonotic spillover and transmission, and how socially differentiated peoples’ interactions with ecosystems and animals affect their exposure to disease. Cross-case analysis highlights how these dynamics vary by ecosystem type, across a range from humid forest to semi-arid savannah; the significance of interacting temporal and spatial scales; and the importance of mosaic and patch dynamics. Ecosystem interactions and services central to different people's livelihoods and well-being include pastoralism and agro-pastoralism, commercial and subsistence crop farming, hunting, collecting food, fuelwood and medicines, and cultural practices. There are synergies, but also tensions and trade-offs, between ecosystem changes that benefit livelihoods and affect disease. Understanding these can inform ‘One Health’ approaches towards managing ecosystems in ways that reduce disease risks and burdens.

This article is part of the themed issue ‘One Health for a changing world: zoonoses, ecosystems and human well-being’.

Rift Valley Fever: A survey of knowledge, attitudes, and practice of slaughterhouse workers and community members in Kabale District, Uganda

Background

Rift Valley Fever virus (RVF) is a zoonotic virus in the Phenuiviridae family. RVF outbreaks can cause significant morbidity and mortality in humans and animals. Following the diagnosis of two RVF cases in March 2016 in southern Kabale district, Uganda, we conducted a knowledge, attitudes and practice (KAP) survey to identify knowledge gaps and at-risk behaviors related to RVF.

Methodology/Principal findings

A multidisciplinary team interviewed 657 community members, including abattoir workers, in and around Kabale District, Uganda. Most participants (90%) had knowledge of RVF and most (77%) cited radio as their primary information source. Greater proportions of farmers (68%), herdsmen (79%) and butchers (88%) thought they were at risk of contracting RVF compared to persons in other occupations (60%, p<0.01). Participants most frequently identified bleeding as a symptom of RVF. Less than half of all participants reported fever, vomiting, and diarrhea as common RVF symptoms in either humans or animals. The level of knowledge about human RVF symptoms did not vary by occupation; however more farmers and butchers (36% and 51%, respectively) had knowledge of RVF symptoms in animals compared to those in other occupations (30%, p<0.01). The use of personal protective equipment (PPE) when handling animals varied by occupation, with 77% of butchers using some PPE and 12% of farmers using PPE. Although most butchers said that they used PPE, most used gumboots (73%) and aprons (60%) and less than 20% of butchers used gloves or eye protection when slaughtering.

Conclusions

Overall, knowledge, attitudes and practice regarding RVF in Kabale District Uganda could be improved through educational efforts targeting specific populations.

Rift Valley Fever (RVF) virus is transmitted to humans from contact with infected livestock and through mosquito bites. Several human cases of RVF were diagnosed in Kabale District, Uganda in March 2016, over 40 years after the last RVF case was identified in Uganda. We administered a knowledge, attitudes, and practice survey to people living in Kabale District, near where the cases occurred. Survey results demonstrated that knowledge, attitudes and practice surrounding RVF could be improved within the community.

Translating Predictions of Zoonotic Viruses for Policymakers

Recent outbreaks of Ebola virus disease and Zika virus disease highlight the need for disseminating accurate predictions of emerging zoonotic viruses to national governments for disease surveillance and response. Although there are published maps for many emerging zoonotic viruses, it is unknown if there is agreement among different models or if they are concordant with national expert opinion. Therefore, we reviewed existing predictions for five high priority emerging zoonotic viruses with national experts in Cameroon to investigate these issues and determine how to make predictions more useful for national policymakers. Predictive maps relied primarily on environmental parameters and species distribution models. Rift Valley fever virus and Crimean-Congo hemorrhagic fever virus predictions differed from national expert opinion, potentially because of local livestock movements. Our findings reveal that involving national experts could elicit additional data to improve predictions of emerging pathogens as well as help repackage predictions for policymakers.

A phytosociological analysis and description of wetland vegetation and ecological factors associated with locations of high mortality for the 2010-11 Rift Valley fever outbreak in South Africa

Rift Valley fever (RVF) is endemic in Africa and parts of the Middle East. It is an emerging zoonotic disease threat to veterinary and public health. Outbreaks of the disease have severe socio-economic impacts. RVF virus emergence is closely associated with specific endorheic wetlands that are utilized by the virus' mosquito vectors. Limited botanical vegetation surveys had been published with regard to RVF virus (RVFV) ecology. We report on a phytosociological classification, analysis and description of wetland vegetation and related abiotic parameters to elucidate factors possibly associated with the 2010-2011 RVFV disease outbreak in South Africa. The study sites were located in the western Free State and adjacent Northern Cape covering an area of ~40,000 km2 with wetlands associated with high RVF mortality rates in livestock. Other study sites included areas where no RVF activity was reported during the 2010-11 RVF outbreak. A total of 129 plots (30 m2) were selected where a visible difference could be seen in the wetland and upland vegetation. The Braun-Blanquet method was used for plant sampling. Classification was done using modified Two-Way Indicator Species Analysis. The vegetation analysis resulted in the identification of eight plant communities, seven sub-communities and two variants. Indirect ordination was carried out using CANOCO to investigate the relationship between species and wetland ecology. The study also identified 5 categories of wetlands including anthropogenic wetlands. Locations of reported RVF cases overlapped sites characterized by high clay-content soils and specific wetland vegetation. These findings indicate ecological and environmental parameters that represent preferred breeding habitat for RVFV competent mosquito vectors.

Spatiotemporal Fluctuations and Triggers of Ebola Virus Spillover

Because the natural reservoir of Ebola virus remains unclear and disease outbreaks in humans have occurred only sporadically over a large region, forecasting when and where Ebola spillovers are most likely to occur constitutes a continuing and urgent public health challenge. We developed a statistical modeling approach that associates 37 human or great ape Ebola spillovers since 1982 with spatiotemporally dynamic covariates including vegetative cover, human population size, and absolute and relative rainfall over 3 decades across sub-Saharan Africa. Our model (area under the curve 0.80 on test data) shows that spillover intensity is highest during transitions between wet and dry seasons; overall, high seasonal intensity occurs over much of tropical Africa; and spillover intensity is greatest at high (>1,000/km²) and very low (<100/km²) human population densities compared with intermediate levels. These results suggest strong seasonality in Ebola spillover from wild reservoirs and indicate particular times and regions for targeted surveillance.

Rift Valley Fever Seroprevalence in Coastal Kenya

Rift Valley fever virus (RVFV) causes severe disease in both animals and humans, resulting in significant economic and public health damages. The objective of this study was to measure RVFV seroprevalence in six coastal Kenyan villages between 2009 and 2011, and characterize individual-, household-, and community-level risk factors for prior RVFV exposure. Sera were tested for anti-RVFV IgG via enzyme-linked immunosorbent assay. Overall, 51 (1.8%; confidence interval [CI₉₅] 1.3-2.3) of 2,871 samples were seropositive for RVFV. Seroprevalence differed significantly among villages, and was highest in Jego Village (18/300; 6.0%; CI₉₅ 3.6-9.3) and lowest in Magodzoni (0/248). Adults were more likely to be seropositive than children (P < 0.001). Seropositive subjects were less likely to own land or a motor vehicle (P < 0.01), suggesting exposure is associated with lower socioeconomic standing (P = 0.03). RVFV exposure appears to be low in coastal Kenya, although with some variability among villages.

Satellite Remote Sensing for Coastal Management: A Review of Successful Applications

Management of coastal and marine natural resources presents a number of challenges as a growing global population and a changing climate require us to find better strategies to conserve the resources on which our health, economy, and overall well-being depend. To evaluate the status and trends in changing coastal resources over larger areas, managers in government agencies and private stakeholders around the world have increasingly turned to remote sensing technologies. A surge in collaborative and innovative efforts between resource managers, academic researchers, and industry partners is becoming increasingly vital to keep pace with evolving changes of our natural resources. Synoptic capabilities of remote sensing techniques allow assessments that are impossible to do with traditional methods. Sixty years of remote sensing research have paved the way for resource management applications, but uncertainties regarding the use of this technology have hampered its use in management fields. Here we review examples of remote sensing applications in the sectors of coral reefs, wetlands, water quality, public health, and fisheries and aquaculture that have successfully contributed to management and decision-making goals.

Spatial, seasonal and climatic predictive models of Rift Valley fever disease across Africa

Understanding the emergence and subsequent spread of human infectious diseases is a critical global challenge, especially for high-impact zoonotic and vector-borne diseases. Global climate and land-use change are likely to alter host and vector distributions, but understanding the impact of these changes on the burden of infectious diseases is difficult. Here, we use a Bayesian spatial model to investigate environmental drivers of one of the most important diseases in Africa, Rift Valley fever (RVF). The model uses a hierarchical approach to determine how environmental drivers vary both spatially and seasonally, and incorporates the effects of key climatic oscillations, to produce a continental risk map of RVF in livestock (as a proxy for human RVF risk). We find RVF risk has a distinct seasonal spatial pattern influenced by climatic variation, with the majority of cases occurring in South Africa and Kenya in the first half of an El Niño year. Irrigation, rainfall and human population density were the main drivers of RVF cases, independent of seasonal, climatic or spatial variation. By accounting more subtly for the patterns in RVF data, we better determine the importance of underlying environmental drivers, and also make space- and time-sensitive predictions to better direct future surveillance resources.This article is part of the themed issue 'One Health for a changing world: zoonoses, ecosystems and human well-being'.

Assessing the performance of remotely-sensed flooding indicators and their potential contribution to early warning for leptospirosis in Cambodia

Remote sensing can contribute to early warning for diseases with environmental drivers, such as flooding for leptospirosis. In this study we assessed whether and which remotely-sensed flooding indicator could be used in Cambodia to study any disease for which flooding has already been identified as an important driver, using leptospirosis as a case study. The performance of six potential flooding indicators was assessed by ground truthing. The Modified Normalized Difference Water Index (MNDWI) was used to estimate the Risk Ratio (RR) of being infected by leptospirosis when exposed to floods it detected, in particular during the rainy season. Chi-square tests were also calculated. Another variable—the time elapsed since the first flooding of the year—was created using MNDWI values and was also included as explanatory variable in a generalized linear model (GLM) and in a boosted regression tree model (BRT) of leptospirosis infections, along with other explanatory variables. Interestingly, MNDWI thresholds for both detecting water and predicting the risk of leptospirosis seroconversion were independently evaluated at -0.3. Value of MNDWI greater than -0.3 was significantly related to leptospirosis infection (RR = 1.61 [1.10–1.52]; χ2 = 5.64, p-value = 0.02, especially during the rainy season (RR = 2.03 [1.25–3.28]; χ2 = 8.15, p-value = 0.004). Time since the first flooding of the year was a significant risk factor in our GLM model (p-value = 0.042). These results suggest that MNDWI may be useful as a risk indicator in an early warning remote sensing tool for flood-driven diseases like leptospirosis in South East Asia.

Drivers for Rift Valley fever emergence in Mayotte: A Bayesian modelling approach

Rift Valley fever (RVF) is a major zoonotic and arboviral hemorrhagic fever. The conditions leading to RVF epidemics are still unclear, and the relative role of climatic and anthropogenic factors may vary between ecosystems. Here, we estimate the most likely scenario that led to RVF emergence on the island of Mayotte, following the 2006-2007 African epidemic. We developed the first mathematical model for RVF that accounts for climate, animal imports and livestock susceptibility, which is fitted to a 12-years dataset. RVF emergence was found to be triggered by the import of infectious animals, whilst transmissibility was approximated as a linear or exponential function of vegetation density. Model forecasts indicated a very low probability of virus endemicity in 2017, and therefore of re-emergence in a closed system (i.e. without import of infected animals). However, the very high proportion of naive animals reached in 2016 implies that the island remains vulnerable to the import of infectious animals. We recommend reinforcing surveillance in livestock, should RVF be reported is neighbouring territories. Our model should be tested elsewhere, with ecosystem-specific data.

Visceral leishmaniasis in Somalia: A review of epidemiology and access to care

Somalia, ravaged by conflict since 1991, has areas endemic for visceral leishmaniasis (VL), a deadly parasitic disease affecting the rural poor, internally displaced, and pastoralists. Very little is known about VL burden in Somalia, where the protracted crisis hampers access to health care. We reviewed evidence about VL epidemiology in Somalia and appraised control options within the context of this fragile state's health system. VL has been reported in Somalia since 1934 and has persisted ever since in foci in the southern parts of the country. The only feasible VL control option is early diagnosis and treatment, currently mostly provided by nonstate actors. The availability of VL care in Somalia is limited and insufficient at best, both in coverage and quality. Precarious security remains a major obstacle to reach VL patients in the endemic areas, and the true VL burden and its impact remain unknown. Locally adjusted, innovative approaches in VL care provision should be explored, without undermining ongoing health system development in Somalia. Ensuring VL care is accessible is a moral imperative, and the limitations of the current VL diagnostic and treatment tools in Somalia and other endemic settings affected by conflict should be overcome.

Drivers of Rift Valley fever epidemics in Madagascar

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.

Anomalous High Rainfall and Soil Saturation as Combined Risk Indicator of Rift Valley Fever Outbreaks, South Africa, 2008-2011

Rift Valley fever (RVF), a zoonotic vectorborne viral disease, causes loss of life among humans and livestock and an adverse effect on the economy of affected countries. Vaccination is the most effective way to protect livestock; however, during protracted interepidemic periods, farmers discontinue vaccination, which leads to loss of herd immunity and heavy losses of livestock when subsequent outbreaks occur. Retrospective analysis of the 2008-2011 RVF epidemics in South Africa revealed a pattern of continuous and widespread seasonal rainfall causing substantial soil saturation followed by explicit rainfall events that flooded dambos (seasonally flooded depressions), triggering outbreaks of disease. Incorporation of rainfall and soil saturation data into a prediction model for major outbreaks of RVF resulted in the correctly identified risk in nearly 90% of instances at least 1 month before outbreaks occurred; all indications are that irrigation is of major importance in the remaining 10% of outbreaks.

Effects of climate change on the occurrence and distribution of livestock diseases

The planet's mean air and ocean temperatures have been rising over the last century because of increasing greenhouse gas (GHG) emissions. These changes have substantial effects on the epidemiology of infectious diseases. We describe direct and indirect processes linking climate change and infectious diseases in livestock with reference to specific case studies. Some of the studies are used to show a positive association between temperature and expansion of the geographical ranges of arthropod vectors (e.g. Culicoides imicola, which transmits bluetongue virus) while others are used to illustrate an opposite trend (e.g. tsetse flies that transmit a range of trypanosome parasites in sub-Saharan Africa). We further describe a positive association between extreme events: droughts and El Niño/southern oscillation (ENSO) weather patterns and Rift Valley fever outbreaks in East Africa and some adaptation practices used to mitigate the impacts of climate change that may increase risk of exposure to infectious pathogens. We conclude by outlining mitigation and adaptation measures that can be used specifically in the livestock sector to minimize the impacts of climate change-associated livestock diseases.

Epidemiologic and Environmental Risk Factors of Rift Valley Fever in Southern Africa from 2008 to 2011

Background: Rift Valley fever (RVF) outbreaks have been associated with periods of widespread and above-normal rainfall over several months. Knowledge on the environmental factors influencing disease transmission dynamics has provided the basis for developing models to predict RVF outbreaks in Africa. From 2008 to 2011, South Africa experienced the worst wave of RVF outbreaks in almost 40 years. We investigated rainfall-associated environmental factors in southern Africa preceding these outbreaks.

Methods: RVF epizootic records obtained from the World Animal Health Information Database (WAHID), documenting livestock species affected, location, and time, were analyzed. Environmental variables including rainfall and satellite-derived normalized difference vegetation index (NDVI) data were collected and assessed in outbreak regions to understand the underlying drivers of the outbreaks.

Results: The predominant domestic vertebrate species affected in 2008 and 2009 were cattle, when outbreaks were concentrated in the eastern provinces of South Africa. In 2010 and 2011, outbreaks occurred in the interior and southern provinces affecting over 16,000 sheep. The highest number of cases occurred between January and April but epidemics occurred in different regions every year, moving from the northeast of South Africa toward the southwest with each progressing year. The outbreaks showed a pattern of increased rainfall preceding epizootics ranging from 9 to 152 days; however, NDVI and rainfall were less correlated with the start of the outbreaks than has been observed in eastern Africa.

Conclusions: Analyses of the multiyear RVF outbreaks of 2008 to 2011 in South Africa indicated that rainfall, NDVI, and other environmental and geographical factors, such as land use, drainage, and topography, play a role in disease emergence. Current and future investigations into these factors will be able to contribute to improving spatial accuracy of models to map risk areas, allowing adequate time for preparation and prevention before an outbreak occurs.

Public Health Benefits from Livestock Rift Valley Fever Control: A Simulation of Two Epidemics in Kenya

In controlling Rift Valley fever, public health sector optimises health benefits by considering cost-effective control options. We modelled cost-effectiveness of livestock RVF control from a public health perspective in Kenya. Analysis was limited to pastoral and agro-pastoral system high-risk areas, for a 10-year period incorporating two epidemics: 2006/2007 and a hypothetical one in 2014/2015. Four integrated strategies (baseline and alternatives), combined from three vaccination and two surveillance options, were compared. Baseline strategy included annual vaccination of 1.2-11% animals plus passive surveillance and monitoring of nine sentinel herds. Compared to the baseline, two alternatives assumed improved vaccination coverage. A herd dynamic RVF animal simulation model produced number of animals infected under each strategy. A second mathematical model implemented in R estimated number people who would be infected by the infected animals. The 2006/2007 RVF epidemic resulted in 3974 undiscounted, unweighted disability adjusted life years (DALYs). Improving vaccination coverage to 41-51% (2012) and 27-33% (2014) 3 years before the hypothetical 2014/2015 outbreak can avert close to 1200 DALYs. Improved vaccinations showed cost-effectiveness (CE) values of US$ 43-53 per DALY averted. The baseline practice is not cost-effective to the public health sector.

Ecological niche modelling of Rift Valley fever virus vectors in Baringo, Kenya

Background

Rift Valley fever (RVF) is a vector-borne zoonotic disease that has an impact on human health and animal productivity. Here, we explore the use of vector presence modelling to predict the distribution of RVF vector species under climate change scenario to demonstrate the potential for geographic spread of Rift Valley fever virus (RVFV).

Objectives

To evaluate the effect of climate change on RVF vector distribution in Baringo County, Kenya, with an aim of developing a risk map for spatial prediction of RVF outbreaks.

Methodology

The study used data on vector presence and ecological niche modelling (MaxEnt) algorithm to predict the effect of climatic change on habitat suitability and the spatial distribution of RVF vectors in Baringo County. Data on species occurrence were obtained from longitudinal sampling of adult mosquitoes and larvae in the study area. We used present (2000) and future (2050) Bioclim climate databases to model the vector distribution.

Results

Model results predicted potential suitable areas with high success rates for Culex quinquefasciatus, Culex univitattus, Mansonia africana, and Mansonia uniformis. Under the present climatic conditions, the lowlands were found to be highly suitable for all the species. Future climatic conditions indicate an increase in the spatial distribution of Cx. quinquefasciatus and M. africana. Model performance was statistically significant.

Conclusion

Soil types, precipitation in the driest quarter, precipitation seasonality, and isothermality showed the highest predictive potential for the four species.

Exposure science in an age of rapidly changing climate: challenges and opportunities

Climate change is anticipated to alter the production, use, release, and fate of environmental chemicals, likely leading to increased uncertainty in exposure and human health risk predictions. Exposure science provides a key connection between changes in climate and associated health outcomes. The theme of the 2015 Annual Meeting of the International Society of Exposure Science-Exposures in an Evolving Environment-brought this issue to the fore. By directing attention to questions that may affect society in profound ways, exposure scientists have an opportunity to conduct "consequential science"-doing science that matters, using our tools for the greater good and to answer key policy questions, and identifying causes leading to implementation of solutions. Understanding the implications of changing exposures on public health may be one of the most consequential areas of study in which exposure scientists could currently be engaged. In this paper, we use a series of case studies to identify exposure data gaps and research paths that will enable us to capture the information necessary for understanding climate change-related human exposures and consequent health impacts. We hope that paper will focus attention on under-developed areas of exposure science that will likely have broad implications for public health.

Spatial Heterogeneity of Habitat Suitability for Rift Valley Fever Occurrence in Tanzania: An Ecological Niche Modelling Approach

BACKGROUND

Despite the long history of Rift Valley fever (RVF) in Tanzania, extent of its suitable habitat in the country remains unclear. In this study we investigated potential effects of temperature, precipitation, elevation, soil type, livestock density, rainfall pattern, proximity to wild animals, protected areas and forest on the habitat suitability for RVF occurrence in Tanzania.

MATERIALS AND METHODS

Presence-only records of 193 RVF outbreak locations from 1930 to 2007 together with potential predictor variables were used to model and map the suitable habitats for RVF occurrence using ecological niche modelling. Ground-truthing of the model outputs was conducted by comparing the levels of RVF virus specific antibodies in cattle, sheep and goats sampled from locations in Tanzania that presented different predicted habitat suitability values.

PRINCIPAL FINDINGS

Habitat suitability values for RVF occurrence were higher in the northern and central-eastern regions of Tanzania than the rest of the regions in the country. Soil type and precipitation of the wettest quarter contributed equally to habitat suitability (32.4% each), followed by livestock density (25.9%) and rainfall pattern (9.3%). Ground-truthing of model outputs revealed that the odds of an animal being seropositive for RVFV when sampled from areas predicted to be most suitable for RVF occurrence were twice the odds of an animal sampled from areas least suitable for RVF occurrence (95% CI: 1.43, 2.76, p < 0.001).

CONCLUSION/SIGNIFICANCE

The regions in the northern and central-eastern Tanzania were more suitable for RVF occurrence than the rest of the regions in the country. The modelled suitable habitat is characterised by impermeable soils, moderate precipitation in the wettest quarter, high livestock density and a bimodal rainfall pattern. The findings of this study should provide guidance for the design of appropriate RVF surveillance, prevention and control strategies which target areas with these characteristics.

Rift Valley fever trasmission dynamics described by compartmental models

Rift Valley fever (RVF) is one of the most important zoonotic Transboundary Animal Diseases able to cross international borders and cause devastating effect on animal health and food security. Climate changes and the presence of competent vectors in the most of the current RVF-free temperate countries strongly support the inclusion of RVF virus (RVFV) among the most significant emerging viral threats for public and animal health. The transmission of RVFV is driven by complex eco-climatic factors making the epidemiology of RVF infection difficult to study and to understand. Mathematical, statistical and spatial models are often used to explain the mechanisms underlying these biological processes, providing new and effective tools to plan measures for public health protection. In this paper we performed a systematic literature review on RVF published papers with the aim of identifying and describing the most recent papers developing compartmental models for the study of RVFV transmission dynamics.

Seasonal forecasting and health impact models: challenges and opportunities

After several decades of intensive research, steady improvements in understanding and modeling the climate system have led to the development of the first generation of operational health early warning systems in the era of climate services. These schemes are based on collaborations across scientific disciplines, bringing together real-time climate and health data collection, state-of-the-art seasonal climate predictions, epidemiological impact models based on historical data, and an understanding of end user and stakeholder needs. In this review, we discuss the challenges and opportunities of this complex, multidisciplinary collaboration, with a focus on the factors limiting seasonal forecasting as a source of predictability for climate impact models.

Has Rift Valley fever virus evolved with increasing severity in human populations in East Africa?

Rift Valley fever (RVF) outbreaks have occurred across eastern Africa from 1912 to 2010 approximately every 4–15 years, most of which have not been accompanied by significant epidemics in human populations. However, human epidemics during RVF outbreaks in eastern Africa have involved 478 deaths in 1998, 1107 reported cases with 350 deaths from 2006 to 2007 and 1174 cases with 241 deaths in 2008. We review the history of RVF outbreaks in eastern Africa to identify the epidemiological factors that could have influenced its increasing severity in humans. Diverse ecological factors influence outbreak frequency, whereas virus evolution has a greater impact on its virulence in hosts. Several factors could have influenced the lack of information on RVF in humans during earlier outbreaks, but the explosive nature of human RVF epidemics in recent years mirrors the evolutionary trend of the virus. Comparisons between isolates from different outbreaks have revealed an accumulation of genetic mutations and genomic reassortments that have diversified RVF virus genomes over several decades. The threat to humans posed by the diversified RVF virus strains increases the potential public health and socioeconomic impacts of future outbreaks. Understanding the shifting RVF epidemiology as determined by its evolution is key to developing new strategies for outbreak mitigation and prevention of future human RVF casualties.

The Epidemiology of Rift Valley Fever in Mayotte: Insights and Perspectives from 11 Years of Data

Rift Valley fever (RVF) is a zoonotic arboviral disease that is a threat to human health, animal health and production, mainly in Sub-Saharan Africa. RVF virus dynamics have been poorly studied due to data scarcity. On the island of Mayotte in the Indian Ocean, off the Southeastern African coast, RVF has been present since at least 2004. Several retrospective and prospective serological surveys in livestock have been conducted over eleven years (2004-15). These data are collated and presented here. Temporal patterns of seroprevalence were plotted against time, as well as age-stratified seroprevalence. Results suggest that RVF was already present in 2004-07. An epidemic occurred between 2008 and 2010, with IgG and IgM peak annual prevalences of 36% in 2008-09 (N = 142, n = 51, 95% CI [17-55]) and 41% (N = 96, n = 39, 95% CI [25-56]), respectively. The virus seems to be circulating at a low level since 2011, causing few new infections. In 2015, about 95% of the livestock population was susceptible (IgG annual prevalence was 6% (N = 584, n = 29, 95% CI [3-10])). Monthly rainfall varied a lot (2-540mm), whilst average temperature remained high with little variation (about 25-30°C). This large dataset collected on an insular territory for more than 10 years, suggesting a past epidemic and a current inter-epidemic period, represents a unique opportunity to study RVF dynamics. Further data collection and modelling work may be used to test different scenarios of animal imports and rainfall pattern that could explain the observed epidemiological pattern and estimate the likelihood of a potential re-emergence.

Geographically weighted discriminant analysis of environmental conditions associated with Rift Valley fever outbreaks in South Africa

Rift Valley fever (RVF) is a zoonotic arboviral infection that has occurred across Africa and parts of the Middle East. Geographically weighted discriminant analysis (GWDA) is a spatially-adaptive extension of traditional discriminant analysis (DA) which has rarely been applied to infectious disease epidemiology research. This study compares the classification performance of GWDA and traditional DA when used to distinguish between locations where livestock are at risk or are not at risk for acquiring RVF virus (RVFV) using 699 case reports of RVF (affecting 18,894 animals) from two outbreaks in South Africa in 2008-2009 and 2010-2011. GWDA produced better results than traditional DA for all bandwidth and kernel combinations. The best GWDA model correctly classified 96.6% of the original data versus 84.5% obtained with traditional DA. With GWDA, false positives decreased from 10.9% to 3.7%, and false negatives decreased from 19.9% to 3.2%.

Association of ecological factors with Rift Valley fever occurrence and mapping of risk zones in Kenya

OBJECTIVE

Rift Valley fever (RVF) is a mosquito-borne infection with great impact on animal and human health. The objectives of this study were to identify ecological factors that explain the risk of RVF outbreaks in eastern and central Kenya and to produce a spatially explicit risk map.

METHODS

The sensitivity of seven selected ecological variables to RVF occurrence was assessed by generalized linear modelling (GLM). Vegetation seasonality variables (from normalized difference vegetation index (NDVI) data) and 'evapotranspiration' (ET) (metrics) were obtained from 0.25-1km MODIS satellite data observations; 'livestock density' (N/km(2)), 'elevation' (m), and 'soil ratio' (fraction of all significant soil types within a certain county as a function of the total area of that county) were used as covariates.

RESULTS

'Livestock density', 'small vegetation integral', and the second principal component of ET were the most significant determinants of RVF occurrence in Kenya (all p ≤ 0.01), with high RVF risk areas identified in the counties of Tana River, Garissa, Isiolo, and Lamu.

CONCLUSIONS

Wet soil fluxes measured with ET and vegetation seasonality variables could be used to map RVF risk zones on a sub-regional scale. Future outbreaks could be better managed if relevant RVF variables are integrated into early warning systems.

Rift Valley fever: current challenges and future prospects

Rift Valley fever (RVF) is a zoonotic, mosquito-borne viral disease that affects human health and causes significant losses in the livestock industry. Recent outbreaks have led to severe human infections with high mortality rates. There are many challenges to applying effective preventive and control measures, including weak infrastructure of health facilities, lack of capacity and support systems for field logistics and communication, access to global expert organizations, and insufficient information on the epidemiological and reservoir status of the RVF virus. The health systems in East African countries are underdeveloped, with gaps in adaptability to new, more accurate and rapid techniques, and well-trained staff that affect their capacity to monitor and evaluate the disease. Surveillance and response systems are inadequate in providing accurate information in a timely manner for decision making to deal with the scope of interrupting the disease transmission by applying mass animal vaccination, and other preventive measures at the early stage of an outbreak. The historical vaccines are unsuitable for use in newborn and gestating livestock, and the recent ones require a booster and annual revaccination. Future live-attenuated RVF vaccines should possess lower safety concerns regardless of the physiologic state of the animal, and provide rapid and long-term immunity after a single dose of vaccination. In the absence of an effective vaccination program, prevention and control measures must be immediately undertaken after an alert is generated. These measures include enforcing and adapting standard protocols for animal trade and movement, extensive vector control, safe disposal of infected animals, and modification of human-animal contact behavior. Directing control efforts on farmers and workers who deal with, handle, or live close to livestock, and focusing on areas with populations at high risk of an epidemic are desirable. Consideration of prevention methods as a first-line strategy against RVF is practical owing to the absence of a human vaccine, particularly under the current high environmental risks and expanding global travel and animal trade. Universal platforms are needed to support coordinated efforts; alert and response operations; exchange of expertise; and disease detection, diagnosis, control, and prevention.

Lessons from the Ebola Outbreak: Action Items for Emerging Infectious Disease Preparedness and Response

As the Ebola outbreak in West Africa wanes, it is time for the international scientific community to reflect on how to improve the detection of and coordinated response to future epidemics. Our interdisciplinary team identified key lessons learned from the Ebola outbreak that can be clustered into three areas: environmental conditions related to early warning systems, host characteristics related to public health, and agent issues that can be addressed through the laboratory sciences. In particular, we need to increase zoonotic surveillance activities, implement more effective ecological health interventions, expand prediction modeling, support medical and public health systems in order to improve local and international responses to epidemics, improve risk communication, better understand the role of social media in outbreak awareness and response, produce better diagnostic tools, create better therapeutic medications, and design better vaccines. This list highlights research priorities and policy actions the global community can take now to be better prepared for future emerging infectious disease outbreaks that threaten global public health and security.

Repetitive dengue outbreaks in East Africa: A proposed phased mitigation approach may reduce its impact

Dengue outbreaks have persistently occurred in eastern African countries for several decades. We assessed each outbreak to identify risk factors and propose a framework for prevention and impact mitigation. Seven out of ten countries in eastern Africa and three islands in the Indian Ocean have experienced dengue outbreaks between 1823 and 2014. Major risk factors associated with past dengue outbreaks include climate, virus and vector genetics and human practices. Appropriate use of dengue diagnostic tools and their interpretation are necessary for both outbreak investigations and sero-epidemiological studies. Serosurvey findings during inter-epidemic periods have not been adequately utilised to prevent re-occurrence of dengue outbreaks. Local weather variables may be used to predict dengue outbreaks, while entomological surveillance can complement other disease-mitigation efforts during outbreaks and identify risk-prone areas during inter-epidemic periods. The limitations of past dengue outbreak responses and the enormous socio-economic impacts of the disease on human health are highlighted. Its repeated occurrence in East Africa refutes previous observations that susceptibility may depend on race. Alternate hypotheses on heterotypic protection among flaviviruses may not be applied to all ecologies. Prevention and mitigation of severe dengue outbreaks should necessarily consider the diverse factors associated with their occurrence. Implementation of phased dengue mitigation activities can enforce timely and judicious use of scarce resources, promote environmental sanitation, and drive behavioural change, hygienic practices and community-based vector control. Understanding dengue epidemiology and clinical symptoms, as determined by its evolution, are significant to preventing future dengue epidemics.

Modelling hotspots of the two dominant Rift Valley fever vectors (Aedes vexans and Culex poicilipes) in Barkédji, Sénégal

BACKGROUND

Climatic and environmental variables were used successfully by using models to predict Rift Valley fever (RVF) virus outbreaks in East Africa. However, these models are not replicable in the West African context due to a likely difference of the dynamic of the virus emergence. For these reasons specific models mainly oriented to the risk mapping have been developed. Hence, the areas of high vector pressure or virus activity are commonly predicted. However, the factors impacting their occurrence are poorly investigated and still unknown. In this study, we examine the impact of climate and environmental factors on the likelihood of occurrence of the two main vectors of RVF in West Africa (Aedes vexans and Culex poicilipes) hotspots.

METHODS

We used generalized linear mixed models taking into account spatial autocorrelation, in order to overcome the default threshold for areas with high mosquito abundance identified by these models. Getis' Gi*(d) index was used to define local adult mosquito abundance clusters (hotspot).

RESULTS

For Culex poicilipes, a decrease of the minimum temperature promotes the occurrence of hotspots, whereas, for Aedes vexans, the likelihood of hotspot occurrence is negatively correlated with relative humidity, maximum and minimum temperatures. However, for the two vectors, proximity to ponds would increase the risk of being in an hotspot area.

CONCLUSIONS

These results may be useful in the improvement of RVF monitoring and vector control management in the Barkedji area.

Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil

Recently, a prototype dengue early warning system was developed to produce probabilistic forecasts of dengue risk three months ahead of the 2014 World Cup in Brazil. Here, we evaluate the categorical dengue forecasts across all microregions in Brazil, using dengue cases reported in June 2014 to validate the model. We also compare the forecast model framework to a null model, based on seasonal averages of previously observed dengue incidence. When considering the ability of the two models to predict high dengue risk across Brazil, the forecast model produced more hits and fewer missed events than the null model, with a hit rate of 57% for the forecast model compared to 33% for the null model. This early warning model framework may be useful to public health services, not only ahead of mass gatherings, but also before the peak dengue season each year, to control potentially explosive dengue epidemics.

Chimpanzee Adenovirus Vaccine Provides Multispecies Protection against Rift Valley Fever

Rift Valley Fever virus (RVFV) causes recurrent outbreaks of acute life-threatening human and livestock illness in Africa and the Arabian Peninsula. No licensed vaccines are currently available for humans and those widely used in livestock have major safety concerns. A ‘One Health’ vaccine development approach, in which the same vaccine is co-developed for multiple susceptible species, is an attractive strategy for RVFV. Here, we utilized a replication-deficient chimpanzee adenovirus vaccine platform with an established human and livestock safety profile, ChAdOx1, to develop a vaccine for use against RVFV in both livestock and humans. We show that single-dose immunization with ChAdOx1-GnGc vaccine, encoding RVFV envelope glycoproteins, elicits high-titre RVFV-neutralizing antibody and provides solid protection against RVFV challenge in the most susceptible natural target species of the virus-sheep, goats and cattle. In addition we demonstrate induction of RVFV-neutralizing antibody by ChAdOx1-GnGc vaccination in dromedary camels, further illustrating the potency of replication-deficient chimpanzee adenovirus vaccine platforms. Thus, ChAdOx1-GnGc warrants evaluation in human clinical trials and could potentially address the unmet human and livestock vaccine needs.

Transmission Dynamics of Rift Valley Fever Virus: Effects of Live and Killed Vaccines on Epizootic Outbreaks and Enzootic Maintenance

Rift Valley fever virus (RVFV) is an arthropod-borne viral pathogen that causes significant morbidity and mortality in small ruminants throughout Africa and the Middle East. Due to the sporadic and explosive nature of RVF outbreaks, vaccination has proved challenging to reduce RVFV infection in the ruminant population. Currently, there are two available types of vaccines, live and killed, in endemic areas. In this study, two mathematical models have been developed to explore the impact of live and killed vaccines on the transmission dynamics of RVFV. We demonstrate in general that vaccination helps reduce the severity of RVF outbreaks and that less delay in implementation and more vaccination attempts and effective vaccines can reduce the outbreak magnitude and the endemic number of RVFV. However, an introduction of a number of ruminants vaccinated by live vaccines in RVFV-free areas may cause an outbreak and RVFV may become endemic if there is sustained use of live vaccines. Other factors that are the important determinants of RVF outbreaks include: unsustained vaccination programs, recruitment of susceptible ruminants, and the seasonal abundance of mosquitoes.

A Preliminary Study to Forecast Japanese Encephalitis Vector Abundance in Paddy Growing Area, with the Aid of Radar Satellite Images

Vector mosquitoes of Japanese encephalitis (JE) breed mostly in rice fields, and human cases occur scattered over extended rural rice-growing areas. From this, one may surmise an ecological connection with the irrigation facilities and paddy cultivation. Furthermore, it has been hypothesized that a particular stage of paddy growth is a premonitory sign that can lead to a markedly increased population of the vector mosquitoes. The present study aimed to forecast the vector abundance by monitoring the paddy growth using remote sensing and geographical information systems. The abundance of the JE vector Culex tritaeniorhynchus peaked when the paddy crop was at its heading stage and dipped when the crop reached the maturing stage. A significant positive correlation was observed between paddy growth and adult density (r = 0.73, p < 0.008). The sigma naught values (σ0) derived from satellite images of paddy fields ranged from -18.3 (during transplantation stage) to approximately -10 (during the noncultivation period). A significant positive correlation was observed between σ0 and paddy growth stages (r = 0.87, p < 0.05) and adult vector density (r = 0.74, p = 0.04). The σ0 value observed during the vegetative and flowering stages of paddy growth ranged from -17.6 to -17.16, at which period the vector density started building up. This could be the spectral signature that denotes the "risk," following which a high vector abundance is expected during heading stage of the paddy.