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

Widening geographic range of Rift Valley fever disease clusters associated with climate change in East Africa

BACKGROUND

Recent epidemiology of Rift Valley fever (RVF) disease in Africa suggests growing frequency and expanding geographic range of small disease clusters in regions that previously had not reported the disease. We investigated factors associated with the phenomenon by characterising recent RVF disease events in East Africa.

METHODS

Data on 100 disease events (2008-2022) from Kenya, Uganda and Tanzania were obtained from public databases and institutions, and modelled against possible geoecological risk factors of occurrence including altitude, soil type, rainfall/precipitation, temperature, normalised difference vegetation index (NDVI), livestock production system, land-use change and long-term climatic variations. Decadal climatic variations between 1980 and 2022 were evaluated for association with the changing disease pattern.

RESULTS

Of 100 events, 91% were small RVF clusters with a median of one human (IQR, 1-3) and three livestock cases (IQR, 2-7). These clusters exhibited minimal human mortality (IQR, 0-1), and occurred primarily in highlands (67%), with 35% reported in areas that had never reported RVF disease. Multivariate regression analysis of geoecological variables showed a positive correlation between occurrence and increasing temperature and rainfall. A 1°C increase in temperature and a 1-unit increase in NDVI, one months prior were associated with increased RVF incidence rate ratios of 1.20 (95% CI 1.1, 1.2) and 1.93 (95% CI 1.01, 3.71), respectively. Long-term climatic trends showed a significant decadal increase in annual mean temperature (0.12-0.3°C/decade, p<0.05), associated with decreasing rainfall in arid and semi-arid lowlands but increasing rainfall trends in highlands (p<0.05). These hotter and wetter highlands showed increasing frequency of RVF clusters, accounting for 76% and 43% in Uganda and Kenya, respectively.

CONCLUSION

These findings demonstrate the changing epidemiology of RVF disease. The widening geographic range of disease is associated with climatic variations, with the likely impact of wider dispersal of virus to new areas of endemicity and future epidemics.

Widening geographic range of Rift Valley fever disease clusters associated with climate change in East Africa

Background

Recent epidemiology of Rift Valley fever (RVF) disease in Africa suggests growing frequency and expanding geographic range of small disease clusters in regions that previously had not reported the disease. We investigated factors associated with the phenomenon by characterizing recent RVF disease events in East Africa.

Methods

Data on 100 disease events (2008 - 2022) from Kenya, Uganda, and Tanzania were obtained from public databases and institutions, and modeled against possible geo-ecological risk factors of occurrence including altitude, soil type, rainfall/precipitation, temperature, normalized difference vegetation index (NDVI), livestock production system, land-use change, and long-term climatic variations. Decadal climatic variations between 1980-2022 were evaluated for association with the changing disease pattern.

Results

Of 100 events, 91% were small RVF clusters with a median of one human (IQR, 1-3) and 3 livestock cases (IQR, 2-7). These clusters exhibited minimal human mortality (IQR 0-1), and occurred primarily in highlands (67%), with 35% reported in areas that had never reported RVF disease. Multivariate regression analysis of geo-ecological variables showed a positive correlation between occurrence and increasing temperature and rainfall. A 1oC increase in temperature and 1-unit increase in NDVI, 1-3 months prior were associated with increased RVF incidence rate ratios (IRR) of 1.20 (95% CI 1.1,1.2) and 9.88 (95% CI 0.85, 119.52), respectively. Long-term climatic trends showed significant decadal increase in annual mean temperature (0.12 to 0.3oC/decade, P<0.05), associated with decreasing rainfall in arid and semi-arid lowlands but increasing rainfall trends in highlands (P<0.05). These hotter and wetter highlands showed increasing frequency of RVF clusters, accounting for 76% and 43% in Uganda and Kenya, respectively.

Conclusion

These findings demonstrate the changing epidemiology of RVF disease. The widening geographic range of disease is associated with climatic variations, with the likely impact of wider dispersal of virus to new areas of endemicity and future epidemics.

Key questions

What is already known on this topic?: Rift Valley fever is recognized for its association with heavy rainfall, flooding, and El Niño rains in the East African region. A growing body of recent studies has highlighted a shifting landscape of the disease, marked by an expanding geographic range and an increasing number of small RVF clusters.What this study adds: This study challenges previous beliefs about RVF, revealing that it predominantly occurs in small clusters rather than large outbreaks, and its association with El Niño is not as pronounced as previously thought. Over 65% of these clusters are concentrated in the highlands of Kenya and Uganda, with 35% occurring in previously unaffected regions, accompanied by an increase in temperature and total rainfall between 1980 and 2022, along with a rise in the annual number of rainy days. Notably, the observed rainfall increases are particularly significant during the short-rains season (October-December), aligning with a secondary peak in RVF incidence. In contrast, the lowlands of East Africa, where typical RVF epidemics occur, display smaller and more varied trends in annual rainfall.How this study might affect research, practice, or policy: The worldwide consequence of the expanding RVF cluster is the broader dispersion of the virus, leading to the establishment of new regions with virus endemicity. This escalation heightens the risk of more extensive extreme-weather-associated RVF epidemics in the future. Global public health institutions must persist in developing preparedness and response strategies for such scenarios. This involves the creation and approval of human RVF vaccines and therapeutics, coupled with a rapid distribution plan through regional banks.

An Integrated Ecological Niche Modelling Framework for Risk Mapping of Peste des Petits Ruminants Virus Exposure in African Buffalo (Syncerus caffer) in the Greater Serengeti-Mara Ecosystem

Peste des petits ruminants (PPR) is a highly contagious viral disease of small ruminants that threatens livelihoods and food security in developing countries and, in some cases, wild ungulate species conservation. The Greater Serengeti-Mara Ecosystem (GSME) encompasses one of the major wildlife populations of PPR virus (PPRV)-susceptible species left on earth, although no clinical disease has been reported so far. This study aimed to gain further knowledge about PPRV circulation in the GSME by identifying which factors predict PPRV seropositivity in African buffalo (Syncerus caffer). Following an ecological niche modeling framework to map host-pathogen distribution, two models of PPRV exposure and buffalo habitat suitability were performed using serological data and buffalo censuses. Western Maasai Mara National Reserve and Western Serengeti National Park were identified as high-risk areas for PPRV exposure in buffalo. Variables related to wildlife-livestock interaction contributed to the higher risk of PPRV seropositivity in buffalo, providing supportive evidence that buffalo acquire the virus through contact with infected livestock. These findings can guide the design of cost-effective PPRV surveillance using buffalo as a sentinel species at the identified high-risk locations. As more intensive studies have been carried out in Eastern GSME, this study highlights the need for investigating PPRV dynamics in Western GSME.

Mechanistic models of Rift Valley fever virus transmission: A systematic review

Rift Valley fever (RVF) is a zoonotic arbovirosis which has been reported across Africa including the northernmost edge, South West Indian Ocean islands, and the Arabian Peninsula. The virus is responsible for high abortion rates and mortality in young ruminants, with economic impacts in affected countries. To date, RVF epidemiological mechanisms are not fully understood, due to the multiplicity of implicated vertebrate hosts, vectors, and ecosystems. In this context, mathematical models are useful tools to develop our understanding of complex systems, and mechanistic models are particularly suited to data-scarce settings. Here, we performed a systematic review of mechanistic models studying RVF, to explore their diversity and their contribution to the understanding of this disease epidemiology. Researching Pubmed and Scopus databases (October 2021), we eventually selected 48 papers, presenting overall 49 different models with numerical application to RVF. We categorized models as theoretical, applied, or grey, depending on whether they represented a specific geographical context or not, and whether they relied on an extensive use of data. We discussed their contributions to the understanding of RVF epidemiology, and highlighted that theoretical and applied models are used differently yet meet common objectives. Through the examination of model features, we identified research questions left unexplored across scales, such as the role of animal mobility, as well as the relative contributions of host and vector species to transmission. Importantly, we noted a substantial lack of justification when choosing a functional form for the force of infection. Overall, we showed a great diversity in RVF models, leading to important progress in our comprehension of epidemiological mechanisms. To go further, data gaps must be filled, and modelers need to improve their code accessibility.

Seroprevalence and associated risk factors of selected zoonotic viral hemorrhagic fevers in Tanzania

OBJECTIVE

To determine the seroprevalence of selected zoonotic viral hemorrhagic fevers (VHFs) and their associated risk factors in Tanzania.

METHODS

Blood samples were collected from consenting outpatients and community members in eight districts selected from five ecological zones of Tanzania. Serum was harvested and tested for the presence of immunoglobulin G (IgG) and M (IgM) antibodies against Crimean-Congo hemorrhagic fever (CCHF), Ebola virus disease (EVD), Marburg virus disease (MVD), Rift Valley fever (RVF), and yellow fever (YF).

RESULTS

The presence of IgM and IgG antibodies against CCHF, EVD, MVD, RVF, and YF was detected in 64 of 500 samples (12.8%). The prevalences of IgM and IgG antibodies to CCHF, EVD, MVD, RFV, and YF were 2.0%, 3.4%, 1.2%, 4.8%, and 1.4%, respectively. Contact with wild animals (OR = 1.2, CI = 1.3-1.6) and keeping goats (OR = 1.3, CI = 1.5-1.9) were significantly associated with RVF, while contact with bats (OR = 1.2, CI = 1.1-1.5) was associated with MVD.

CONCLUSION

The findings of this study provide evidence of exposure to CCHF, EVD, MVD, RVF, and YF in Tanzania. Since most of these VHFs occurred without apparent clinical forms of the disease, these findings call for the need to strengthen the surveillance system and management of febrile illnesses in Tanzania.

Risk assessment for the Rift Valley fever occurrence in China: Special concern in south-west border areas

Rift Valley fever (RVF) is a mosquito-borne zoonotic disease. Since its first outbreak in 1930, RVF epidemics have caused huge economic losses and public health impacts in Africa. In 2000, RVF became a disease of global concern as it spread to the Arabian Peninsula. In our study, a Geographic Information System-based risk assessment for the occurrence of Rift Valley fever in China was established by means of ecological niche modelling. Based on occurrence records (RVF records from FAO EMPRES-i, vector records from literatures and GBIF) and high-resolution environmental layers, the prediction maps of RVF occurrence probability and distribution of five potential RVF vectors in China were modelled using Maxent. An internal validation was adopted for model verification, and high AUC values were obtained (0.918 for RVF and 0.837-0.992 for vectors). By overlaying the RVF prediction map with the combined RVF vector prediction map using Fuzzy overlay tool ('AND' operator) of ArcMap 10.2, we got the first risk map of possible RVF vector transmission. This map was further overlaid with the latest livestock distribution map ('AND' operator) to generate the second risk map of possible RVF threat to domestic livestock. The south-west border provinces in China, Yunnan, Guangxi and Tibet were predicted to have a high possibility of RVF occurrence. Conditions conducive to the local amplification of RVF also exist in these areas. Temperature seasonality, mean temperature of dry season and precipitation of the driest month were considered as key environmental variables for RVF, and common environmental conditions were found conductive for vectors. It is suggested to establish proper surveillance systems in south-west border areas to minimize the possibility of RVF invasion. Our findings can serve as a valuable reference for prevention measures to be implemented.

Selected wetland soil properties correlate to Rift Valley fever livestock mortalities reported in 2009-10 in central South Africa

Outbreaks of Rift Valley fever have devastating impacts on ruminants, humans, as well as on regional and national economies. Although numerous studies on the impact and outbreak of Rift Valley fever exist, relatively little is known about the role of environmental factors, especially soil, on the aestivation of the virus. This study thus selected 22 sites for study in central South Africa, known to be the recurrent epicenter of widespread Rift Valley fever outbreaks in Southern Africa. Soils were described, sampled and analyzed in detail at each site. Of all the soil variables analyzed for, only eight (cation exchange capacity, exchangeable Ca²⁺, exchangeable K⁺, exchangeable Mg²⁺, soluble Ca²⁺, medium sand, As, and Br) were statistically identified to be potential indicators of sites with reported Rift Valley fever mortalities, as reported for the 2009–2010 Rift Valley fever outbreak. Four soil characteristics (exchangeable K⁺, exchangeable Mg²⁺, medium sand, and Br) were subsequently included in a discriminant function that could potentially be used to predict sites that had reported Rift Valley fever-associated mortalities in livestock. This study therefore constitutes an initial attempt to predict sites prone to Rift Valley fever livestock mortality from soil properties and thus serves as a basis for broader research on the interaction between soil, mosquitoes and Rift Valley fever virus. Future research should include other environmental components such as vegetation, climate, and water properties as well as correlating soil properties with floodwater Aedes spp. abundance and Rift Valley fever virus prevalence.

Ecological niche modelling to estimate the distribution of Culicoides, potential vectors of bluetongue virus in Senegal

BACKGROUND

Vector-borne diseases are among the leading causes of morbidity and mortality in humans and animals. In the Afrotropical region, some are transmitted by Culicoides, such as Akabane, bluetongue, epizootic haemorrhagic fever and African horse sickness viruses. Bluetongue virus infection has an enormous impact on ruminant production, due to its high morbidity and mortality rates.

METHODS

A nationwide Culicoides trapping campaign was organized at the end of the 2012 rainy season in Senegal. A Maximum Entropy approach (MaxEnt), Boosted Regression Tree (BRT) method and Ecological Niche Factor Analysis (ENFA) were used to develop a predictive spatial model for the distribution of Culicoides, using bio-climatic variables, livestock densities and altitude.

RESULTS

The altitude, maximum temperature of the warmest month, precipitation of the warmest quarter, mean temperature of the wettest quarter, temperature seasonality, precipitation of the wettest quarter and livestock density were among the most important factors to predict suitable habitats of Culicoides. Culicoides occurrences were, in most of the cases, positively correlated to precipitation variables and livestock densities; and negatively correlated to the altitude and temperature indices. The Niayes area and the Groundnut basin were the most suitable habitats predicted.

CONCLUSION

We present ecological niche models for different Culicoides species, namely C. imicola, C. oxystoma, C. enderleini and C. miombo, potential vectors of bluetongue virus, on a nationwide scale in Senegal. Through our modelling approach, we were able to determine the effect of bioclimatic variables on Culicoides habitats and were able to generate maps for the occurrence of Culicoides species. This information will be helpful in developing risk maps for disease outbreaks.

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.

Phylogeography and niche modelling: reciprocal enlightenment

Phylogeography examines the spatial genetic structure of species. Environmental niche modelling (or ecological niche modelling; ENM) examines the environmental limits of a species’ ecological niche. These two fields have great potential to be used together. ENM can shed light on how phylogeographical patterns develop and help identify possible drivers of spatial structure that need to be further investigated. Specifically, ENM can be used to test for niche differentiation among clades, identify factors limiting individual clades and identify barriers and contact zones. It can also be used to test hypotheses regarding the effects of historical and future climate change on spatial genetic patterns by projecting niches using palaeoclimate or future climate data. Conversely, phylogeographical information can populate ENM with within-species genetic diversity. Where adaptive variation exists among clades within a species, modelling their niches separately can improve predictions of historical distribution patterns and future responses to climate change. Awareness of patterns of genetic diversity in niche modelling can also alert conservationists to the potential loss of genetically diverse areas in a species’ range. Here, we provide a simplistic overview of both fields, and focus on their potential for integration, encouraging researchers on both sides to take advantage of the opportunities available.

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.

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.

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.

Inferring the geographic origin of a range expansion: Latitudinal and longitudinal coordinates inferred from genomic data in an ABC framework with the program x-origin

Climatic or environmental change is not only driving distributional shifts in species today, but it has also caused distributions to expand and contract in the past. Inferences about the geographic locations of past populations especially regions that served as refugia (i.e., source populations) and migratory routes are a challenging endeavour. Refugial areas may be evidenced from fossil records or regions of temporal stability inferred from ecological niche models. Genomic data offer an alternative and broadly applicable source of information about the locality of refugial areas, especially relative to fossil data, which are either unavailable or incomplete for most species. Here, we present a pipeline we developed (called x-origin) for statistically inferring the geographic origin of range expansion using a spatially explicit coalescent model and an approximate Bayesian computation testing framework. In addition to assessing the probability of specific latitudinal and longitudinal coordinates of refugial or source populations, such inferences can also be made accounting for the effects of temporal and spatial environmental heterogeneity, which may impact migration routes. We demonstrate x-origin with an analysis of genomic data collected in the Collared pika that underwent postglacial expansion across Alaska, as well as present an assessment of its accuracy under a known model of expansion to validate the approach.