Prediction of a Rift Valley fever outbreak

Broadscale spatial synchrony in a West Nile virus mosquito vector across multiple timescales

Insects often exhibit irruptive population dynamics determined by environmental conditions. We examine if populations of the Culex tarsalis mosquito, a West Nile virus (WNV) vector, fluctuate synchronously over broad spatial extents and multiple timescales and whether climate drives synchrony in Cx. tarsalis, especially at annual timescales, due to the synchronous influence of temperature, precipitation, and/or humidity. We leveraged mosquito collections across 9 National Ecological Observatory Network (NEON) sites distributed in the interior West and Great Plains region USA over a 45-month period, and associated gridMET climate data. We utilized wavelet phasor mean fields and wavelet linear models to quantify spatial synchrony for mosquitoes and climate and to calculate the importance of climate in explaining Cx. tarsalis synchrony. We also tested whether the strength of spatial synchrony may vary directionally across years. We found significant annual synchrony in Cx. tarsalis, and short-term synchrony during a single period in 2018. Mean minimum temperature was a significant predictor of annual Cx. tarsalis spatial synchrony, and we found a marginally significant decrease in annual Cx. tarsalis synchrony. Significant Cx. tarsalis synchrony during 2018 coincided with an anomalous increase in precipitation. This work provides a valuable step toward understanding broadscale synchrony in a WNV vector.

Assessing the vulnerability of food supply chains to climate change-induced disruptions

Climate change is one of the most significant challenges worldwide. There is strong evidence from research that climate change will impact several food chain-related elements such as agricultural output, incomes, prices, food access, food quality, and food safety. This scoping review seeks to outline the state of knowledge of the food supply chain's vulnerability to climate change and to identify existing literature that may guide future research, policy, and decision-making aimed at enhancing the resilience of the food supply chain. A total of 1526 publications were identified using the SCOPUS database, of which 67 were selected for the present study. The vulnerability assessment methods as well as the adaptation and resilience measures that have been employed to alleviate the impact of climate change in the food supply chain were discussed. The results revealed a growing number of publications providing evidence of the weakening of the food supply chain due to climate change and extreme weather events. Our assessment demonstrated the need to broaden research into the entire food supply chain and various forms of climatic variability because most studies have concentrated on the relationships between climatic fluctuations (especially extreme rainfall, temperatures, and drought) and production. A lack of knowledge about the effects of climate change on the food supply chain and the underlying socio-economic consequences could result in underperformance or failure of the food supply chain.

Ability of a dynamical climate sensitive disease model to reproduce historical Rift Valley Fever outbreaks over Africa

Rift Valley Fever (RVF) is a zoonosis transmitted by Aedes and Culex mosquitoes, and is considered a priority pathogen by the WHO. RVF epidemics mostly occur in Africa and can decimate livestock herds, causing significant economic losses and posing health risks for humans. RVF transmission is associated with the occurrence of El Niño events that cause floods in eastern Africa and favour the emergence of mosquitoes in wetlands. Different risk models have been developed to forecast RVF transmission risk but very few studies have validated models at pan-African scale. This study aims to validate the skill of the Liverpool Rift Valley Fever model (LRVF) in reproducing RVF epidemics over Africa and to explore the relationship between simulated climatic suitability for RVF transmission and large-scale climate modes of variability such as the El Niño Southern Oscillation (ENSO) and the Dipole Mode Index (DMI). Our results show that the LRVF model correctly simulates RVF transmission hotspots and reproduces large epidemics that affected African countries. LRVF was able to correctly reproduce major RVF epidemics in Somalia, Kenya, Zambia and to a lesser extent for Mauritania and Senegal. The positive phases of ENSO and DMI are associated with an increased risk of RVF over the Horn of Africa, with important time lags. Following research activities should focus on the development of predictive modelling systems at different time scales.

Zoonoses research in Somalia: A scoping review using a One Health approach

Zoonoses are likely to cause a substantial burden on both human and animal health systems in Somalia, given the close proximity between the pastoralist majority and their livestock. However, decades of instability leading to weak disease surveillance have meant that data on the burden of zoonoses is lacking. The aim of this scoping review was to assess and synthesize the available literature on the presence and burden of zoonoses in Somalia. We used keywords to search Web of Science for relevant publications. Studies were included if they contained relevant data on a zoonosis and were undertaken in Somalia or were undertaken in another country where exposure could reasonably be assumed to have occurred in Somalia (e.g., migrants/refugees, returning soldiers, exported animals). Studies were not included if they focused on Somali ethnic communities permanently living elsewhere or if zoonotic aspects were not considered. We extracted data on disease(s) reported, geographic focus, data reported (human, animal, environment), study design and author affiliation. A total of 22 zoonotic infections were documented in 76 publications. The most frequently studied diseases were Rift Valley Fever (n = 15, 17%), brucellosis (n = 13, 14%) and hepatitis E (n = 10, 11%). Around 30% of papers reported data from relevant populations outside Somalia. Only 18 papers undertook laboratory analysis within Somalia. Most papers reported data on humans (45%) and animals (36%) with limited research on the environmental domain. Descriptive studies (47%) dominated and most were led by non-Somali researchers (89% in first authors and 95% of last authors). This study highlights the need for well-designed zoonoses research in Somalia supported by capacity building of local researchers and investments in diagnostic laboratories.

Ecological and subject-level drivers of interepidemic Rift Valley fever virus exposure in humans and livestock in Northern Kenya

Nearly a century after the first reports of Rift Valley fever (RVF) were documented in Kenya, questions on the transmission dynamics of the disease remain. Specifically, data on viral maintenance in the quiescent years between epidemics is limited. We implemented a cross-sectional study in northern Kenya to determine the seroprevalence, risk factors, and ecological predictors of RVF in humans and livestock during an interepidemic period. Six hundred seventy-six human and 1,864 livestock samples were screened for anti-RVF Immunoglobulin G (IgG). Out of the 1,864 livestock samples tested for IgG, a subset of 1,103 samples was randomly selected for additional testing to detect the presence of anti-RVFV Immunoglobulin M (IgM). The anti-RVF virus (RVFV) IgG seropositivity in livestock and humans was 21.7% and 28.4%, respectively. RVFV IgM was detected in 0.4% of the livestock samples. Participation in the slaughter of livestock and age were positively associated with RVFV exposure in humans, while age was a significant factor in livestock. We detected significant interaction between rainfall and elevation's influence on livestock seropositivity, while in humans, elevation was negatively associated with RVF virus exposure. The linear increase of human and livestock exposure with age suggests an endemic transmission cycle, further corroborated by the detection of IgM antibodies in livestock.

Multifunctional human monoclonal antibody combination mediates protection against Rift Valley fever virus at low doses

The zoonotic Rift Valley fever virus (RVFV) can cause severe disease in humans and has pandemic potential, yet no approved vaccine or therapy exists. Here we describe a dual-mechanism human monoclonal antibody (mAb) combination against RVFV that is effective at minimal doses in a lethal mouse model of infection. We structurally analyze and characterize the binding mode of a prototypical potent Gn domain-A-binding antibody that blocks attachment and of an antibody that inhibits infection by abrogating the fusion process as previously determined. Surprisingly, the Gn domain-A antibody does not directly block RVFV Gn interaction with the host receptor low density lipoprotein receptor-related protein 1 (LRP1) as determined by a competitive assay. This study identifies a rationally designed combination of human mAbs deserving of future investigation for use in humans against RVFV infection. Using a two-pronged mechanistic approach, we demonstrate the potent efficacy of a rationally designed combination mAb therapeutic.

A highly potent human neutralizing antibody prevents vertical transmission of Rift Valley fever virus in a rat model

Rift Valley fever virus (RVFV) is an emerging mosquito-transmitted virus that circulates in livestock and humans in Africa and the Middle East. Outbreaks lead to high rates of miscarriages in domesticated livestock. Women are also at risk of vertical virus transmission and late-term miscarriages. MAb RVFV-268 is a highly potent recombinant neutralizing human monoclonal antibody that targets RVFV. Here we show that mAb RVFV-268 reduces viral replication in rat placenta explant cultures and prevents vertical transmission in a rat model of congenital RVF. Passive transfer of mAb RVFV-268 from mother to fetus occurs as early as 6 h after administration and persists through 24 h. Administering mAb RVFV-268 2 h prior to RVFV challenge or 24 h post-challenge protects the dams and offspring from RVFV infection. These findings support mAb RVFV-268 as a pre- and post-infection treatment to subvert RVFV infection and vertical transmission, thus protecting the mother and offspring.

Modeling the effectiveness of targeting Rift Valley fever virus vaccination using imperfect network information

Livestock movements contribute to the spread of several infectious diseases. Data on livestock movements can therefore be harnessed to guide policy on targeted interventions for controlling infectious livestock diseases, including Rift Valley fever (RVF)-a vaccine-preventable arboviral fever. Detailed livestock movement data are known to be useful for targeting control efforts including vaccination. These data are available in many countries, however, such data are generally lacking in others, including many in East Africa, where multiple RVF outbreaks have been reported in recent years. Available movement data are imperfect, and the impact of this uncertainty in the utility of movement data on informing targeting of vaccination is not fully understood. Here, we used a network simulation model to describe the spread of RVF within and between 398 wards in northern Tanzania connected by cattle movements, on which we evaluated the impact of targeting vaccination using imperfect movement data. We show that pre-emptive vaccination guided by only market movement permit data could prevent large outbreaks. Targeted control (either by the risk of RVF introduction or onward transmission) at any level of imperfect movement information is preferred over random vaccination, and any improvement in information reliability is advantageous to their effectiveness. Our modeling approach demonstrates how targeted interventions can be effectively used to inform animal and public health policies for disease control planning. This is particularly valuable in settings where detailed data on livestock movements are either unavailable or imperfect due to resource limitations in data collection, as well as challenges associated with poor compliance.

Geostatistical Modeling and Prediction of Rift Valley Fever Seroprevalence among Livestock in Uganda

Uganda reported cases of Rift Valley fever virus (RVFV) for the first time in almost 50 years in 2016, following an outbreak of Rift Valley fever (RVF) that caused four human infections, two of which resulted in death. Subsequent outbreak investigation serosurveys found high seroprevalence of IgG antibodies without evidence of acute infection or IgM antibodies, suggesting the possibility of undetected RVFV circulation prior to the outbreak. After the 2016 outbreak investigation, a serosurvey was conducted in 2017 among domesticated livestock herds across Uganda. Sampling data were incorporated into a geostatistical model to estimate RVF seroprevalence among cattle, sheep, and goats. Variables resulting in the best fit to RVF seroprevalence sampling data included annual variability in monthly precipitation and enhanced vegetation index, topographic wetness index, log human population density percent increase, and livestock species. Individual species RVF seroprevalence prediction maps were created for cattle, sheep, and goats, and a composite livestock prediction was created based on the estimated density of each species across the country. Seroprevalence was greater in cattle compared with sheep and goats. Predicted seroprevalence was greatest in the central and northwestern quadrant of the country, surrounding Lake Victoria, and along the Southern Cattle Corridor. We identified areas that experienced conditions conducive to potential increased RVFV circulation in 2021 in central Uganda. An improved understanding of the determinants of RVFV circulation and locations with high probability of elevated RVF seroprevalence can guide prioritization of disease surveillance and risk mitigation efforts.

Identifying the genetic basis of viral spillover using Lassa virus as a test case

The rate at which zoonotic viruses spill over into the human population varies significantly over space and time. Remarkably, we do not yet know how much of this variation is attributable to genetic variation within viral populations. This gap in understanding arises because we lack methods of genetic analysis that can be easily applied to zoonotic viruses, where the number of available viral sequences is often limited, and opportunistic sampling introduces significant population stratification. Here, we explore the feasibility of using patterns of shared ancestry to correct for population stratification, enabling genome-wide association methods to identify genetic substitutions associated with spillover into the human population. Using a combination of phylogenetically structured simulations and Lassa virus sequences collected from humans and rodents in Sierra Leone, we demonstrate that existing methods do not fully correct for stratification, leading to elevated error rates. We also demonstrate, however, that the Type I error rate can be substantially reduced by confining the analysis to a less-stratified region of the phylogeny, even in an already-small dataset. Using this method, we detect two candidate single-nucleotide polymorphisms associated with spillover in the Lassa virus polymerase gene and provide generalized recommendations for the collection and analysis of zoonotic viruses.

Epidemiology of Ebolaviruses from an Etiological Perspective

Since the inception of the ebolavirus in 1976, 32 outbreaks have resulted in nearly 15,350 deaths in more than ten countries of the African continent. In the last decade, the largest (2013-2016) and second largest (2018-2020) ebolavirus outbreaks have occurred in West Africa (mainly Guinea, Liberia, and Sierra Leone) and the Democratic Republic of the Congo, respectively. The 2013-2016 outbreak indicated an alarming geographical spread of the virus and was the first to qualify as an epidemic. Hence, it is imperative to halt ebolavirus progression and develop effective countermeasures. Despite several research efforts, ebolaviruses' natural hosts and secondary reservoirs still elude the scientific world. The primary source responsible for infecting the index case is also unknown for most outbreaks. In this review, we summarize the history of ebolavirus outbreaks with a focus on etiology, natural hosts, zoonotic reservoirs, and transmission mechanisms. We also discuss the reasons why the African continent is the most affected region and identify steps to contain this virus.

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.

Projecting vaccine demand and impact for emerging zoonotic pathogens

BACKGROUND

Despite large outbreaks in humans seeming improbable for a number of zoonotic pathogens, several pose a concern due to their epidemiological characteristics and evolutionary potential. To enable effective responses to these pathogens in the event that they undergo future emergence, the Coalition for Epidemic Preparedness Innovations is advancing the development of vaccines for several pathogens prioritized by the World Health Organization. A major challenge in this pursuit is anticipating demand for a vaccine stockpile to support outbreak response.

METHODS

We developed a modeling framework for outbreak response for emerging zoonoses under three reactive vaccination strategies to assess sustainable vaccine manufacturing needs, vaccine stockpile requirements, and the potential impact of the outbreak response. This framework incorporates geographically variable zoonotic spillover rates, human-to-human transmission, and the implementation of reactive vaccination campaigns in response to disease outbreaks. As proof of concept, we applied the framework to four priority pathogens: Lassa virus, Nipah virus, MERS coronavirus, and Rift Valley virus.

RESULTS

Annual vaccine regimen requirements for a population-wide strategy ranged from > 670,000 (95% prediction interval 0-3,630,000) regimens for Lassa virus to 1,190,000 (95% PrI 0-8,480,000) regimens for Rift Valley fever virus, while the regimens required for ring vaccination or targeting healthcare workers (HCWs) were several orders of magnitude lower (between 1/25 and 1/700) than those required by a population-wide strategy. For each pathogen and vaccination strategy, reactive vaccination typically prevented fewer than 10% of cases, because of their presently low R₀ values. Targeting HCWs had a higher per-regimen impact than population-wide vaccination.

CONCLUSIONS

Our framework provides a flexible methodology for estimating vaccine stockpile needs and the geographic distribution of demand under a range of outbreak response scenarios. Uncertainties in our model estimates highlight several knowledge gaps that need to be addressed to target vulnerable populations more accurately. These include surveillance gaps that mask the true geographic distribution of each pathogen, details of key routes of spillover from animal reservoirs to humans, and the role of human-to-human transmission outside of healthcare settings. In addition, our estimates are based on the current epidemiology of each pathogen, but pathogen evolution could alter vaccine stockpile requirements.

An unusually long Rift valley fever inter-epizootic period in Zambia: Evidence for enzootic virus circulation and risk for disease outbreak

Rift valley fever (RVF) is a mosquito-borne disease of animals and humans. Although RVF outbreaks are usually reported at 5-15-year intervals in sub-Saharan Africa, Zambia has experienced an unusually long inter-epizootic/-epidemic period of more than three decades. However, serological evidence of RVF virus (RVFV) infection in domestic ruminants during this period underscores the need for comprehensive investigation of the mechanisms of virus perpetuation and disease emergence. Mosquitoes (n = 16,778) captured from eight of the ten provinces of Zambia between April 2014 and May 2019 were pooled (n = 961) and screened for RVFV genome by a pan-phlebo RT-PCR assay. Aedes mosquito pools (n = 85) were further screened by nested RT-PCR assay. Sera from sheep (n = 13), goats (n = 259) and wild ungulates (n = 285) were screened for RVFV antibodies by ELISA while genome detection in pooled sera (n = 276) from domestic (n = 248) and wild ungulates (n = 37) was performed by real-time RT-PCR assay. To examine the association between the long inter-epizootic period and climatic variables, we examined El Niño-Southern Oscillation indices, precipitation anomalies, and normalized difference vegetation index. We then derived RVF risk maps by exploring climatic variables that would favor emergence of primary RVFV vectors. While no RVFV genome could be detected in pooled mosquito and serum samples, seroprevalence was significantly high (OR = 8.13, 95% CI [4.63–14.25]) in wild ungulates (33.7%; 96/285) compared to domestic ruminants (5.6%; 16/272). Retrospective analysis of RVF epizootics in Zambia showed a positive correlation between anomalous precipitation (La Niña) and disease emergence. On risk mapping, whilst northern and eastern parts of the country were at high risk, domestic ruminant population density was low (< 21 animals/km²) in these areas compared to low risk areas (>21 animals/km²). Besides evidence of silent circulation of RVFV and the risk of disease emergence in some areas, wildlife may play a role in the maintenance of RVFV in Zambia.

Rift valley fever (RVF) is an important mosquito borne disease of humans and ruminants. RVF is endemic in sub-Saharan Africa where disease outbreaks are frequently reported in humans and animals. For RVF outbreaks to occur, there has to be presence of the host (animals or humans) and favorable climatic conditions that favor emergence of RVF virus vectors (mosquitoes). Understanding this complex interaction enables us to predict future disease outbreaks and map RVF high risk areas. Above normal rainfall and floods will usually trigger RVF outbreaks. In this study, we conducted surveillance for RVF in mosquitoes, domestic and wild ruminants. We then examined climatic conditions that may have been responsible for past RVF outbreaks and the unusually (>30 years) long inter-epizootic period. Finally, we derived RVF risk maps for Zambia using a combination of climatic variables. We found evidence of RVF infection in both wild and domestic ruminants while there was a positive correlation between past RVF outbreaks and above-normal rainfall. On risk mapping, we found favorable conditions (i.e. high rainfall and risk of flooding) for RVF emergence in northern and eastern parts of the country. Studies like this are important in planning surveillance and disease control programs.

Temporal Correlation Between Urban Microclimate, Vector Mosquito Abundance, and Dengue Cases

Dengue Hemorrhagic Fever (DHF) is a major mosquito-borne viral disease. Studies have reported a strong correlation between weather, the abundance of Aedes aegypti, the vector of DHF virus, and dengue incidence. However, this conclusion has been based on the general climate pattern of wide regions. In general, however, the human population, level of infrastructure, and land-use change in rural and urban areas often produce localized climate patterns that may influence the interaction between climate, vector abundance, and dengue incidence. Thoroughly understanding this correlation will allow the development of a customized and precise local early warning system. To achieve this purpose, we conducted a cohort study, during January-December 2017, in 16 districts in Bandung, West Java, Indonesia. In the selected areas, local weather stations and modified light mosquito traps were set up to obtain data regarding daily weather and the abundance of adult female Ae. aegypti. A generalized linear model was applied to analyze the effect of local weather and female adult Ae. aegypti on the number of dengue cases. The result showed a significant non-linear correlation among mosquito abundance, maximum temperature, and dengue cases. Using our model, the data showed that the addition of a single adult Ae. aegypti mosquito increased the risk of dengue infection by 1.8%, while increasing the maximum temperature by one degree decreased the risk by 17%. This finding suggests specific actionable insights needed to supplement existing mosquito eradication programs.

Climate change and zoonoses: A review of the current status, knowledge gaps, and future trends

Emerging infectious diseases (EIDs), especially those with zoonotic potential, are a growing threat to global health, economy, and safety. The influence of global warming and geoclimatic variations on zoonotic disease epidemiology is evident by alterations in the host, vector, and pathogen dynamics and their interactions. The objective of this article is to review the current literature on the observed impacts of climate change on zoonoses and discuss future trends. We evaluated several climate models to assess the projections of various zoonoses driven by the predicted climate variations. Many climate projections revealed potential geographical expansion and the severity of vector-borne, waterborne, foodborne, rodent-borne, and airborne zoonoses. However, there are still some knowledge gaps, and further research needs to be conducted to fully understand the magnitude and consequences of some of these changes. Certainly, by understanding the impact of climate change on zoonosis emergence and distribution, we could better plan for climate mitigation and climate adaptation strategies.

Climate Conditions During a Rift Valley Fever Post-epizootic Period in Free State, South Africa, 2014–2019

Rift Valley fever virus (RVFV) activity in Southern Africa tends to occur during periods of sustained elevated rainfall, cooler than normal conditions, and abundant vegetation cover creating ideal conditions for the increase and propagation of populations of RVFV mosquito vectors. These climatic and ecological conditions are modulated by large-scale tropical-wide El Niño–Southern Oscillation (ENSO) phenomena. The aim of this 5-year study was to investigate climatic conditions during Rift Valley fever “post-epizootic” period in Free State province of the Republic of South Africa, which historically experienced the largest RVF outbreaks in this country. We collected satellite-derived rainfall, land surface temperature (LST), and normalized difference vegetation index (NDVI) data since 2014 to understand broad environmental conditions in the years following a period of sustained and widespread large RVF outbreaks (2008–2011) in the region. We found this post-epizootic/interepizootic period to be characterized by below-normal rainfall (~-500 mm), above LSTs (~+12°C), depressed NDVI (60% below normal), and severe drought as manifested particularly during the 2015–2016 growing season. Such conditions reduce the patchwork of appropriate habitats available for emergence of RVFV vectors and diminish chances of RVFV activity. However, the 2016–2017 growing season saw a marked return to somewhat wetter conditions without any reported RVFV transmission. In general, the aggregate vector collections during this 5-year period follow patterns observed in climate measurements. During the 2017–2018 growing season, late and seasonally above average rainfall resulted in a focal RVF outbreak in one location in the study region. This unanticipated event is an indicator of cryptic RVF activity during post-epizootic period and may be a harbinger of RVFV activity in the coming years.

Global implications of biodiversity loss on pandemic disease: COVID-19

Unpredictable climate changes and adverse effects on the planetary health due to environmental degradation have led to the rise of concerns regarding human wellness in the recent days. Coronavirus disease 2019 (COVID-19) is said to be originated from wildlife species and represents a significant threat to human health, social, food, and economic security. However, understanding the underlying factors behind the emergence is still rudimentary. This study has made efforts to understand the relationship between the drivers that causes the emergence of infectious diseases (EID). The recent biodiversity crisis that has a severe impact on planetary health is a new contributory factor for the emergence of COVID-19. The biodiversity crisis is an outcome of the land use and land cover (LULC) change, contributing to climate change. In the overall global LULC, 60% are associated with direct human activities and 40% indirect causes such as climate change. Climate change is one of the critical factors that induce landcover change, associated with increasing consumerism, environmental pollution, excessive livestock production, population explosion, and food production. Geospatial techniques provide a viable solution for monitoring the key drivers responsible for EID, such as climate characteristics, LULC, global land cover under food production, and locations affected by infectious diseases in the past. The study’s main objective is to discuss the possibilities of evolving novel solutions to approach the forecasting of emerging infectious disease spread and its mitigation, bridging the sectors and stakeholders, with due relevance to sustainable development goals (SDGs) and other dimensions from global to community levels.

Paving the way for human vaccination against Rift Valley fever virus: A systematic literature review of RVFV epidemiology from 1999 to 2021

BACKGROUND

Rift Valley fever virus (RVFV) is a lethal threat to humans and livestock in many parts of Africa, the Arabian Peninsula, and the Indian Ocean. This systematic review's objective was to consolidate understanding of RVFV epidemiology during 1999-2021 and highlight knowledge gaps relevant to plans for human vaccine trials.

METHODOLOGY/PRINCIPAL FINDINGS

The review is registered with PROSPERO (CRD42020221622). Reports of RVFV infection or exposure among humans, animals, and/or vectors in Africa, the Arabian Peninsula, and the Indian Ocean during the period January 1999 to June 2021 were eligible for inclusion. Online databases were searched for publications, and supplemental materials were recovered from official reports and research colleagues. Exposures were classified into five groups: 1) acute human RVF cases, 2) acute animal cases, 3) human RVFV sero-surveys, 4) animal sero-surveys, and 5) arthropod infections. Human risk factors, circulating RVFV lineages, and surveillance methods were also tabulated. In meta-analysis of risks, summary odds ratios were computed using random-effects modeling. 1104 unique human or animal RVFV transmission events were reported in 39 countries during 1999-2021. Outbreaks among humans or animals occurred at rates of 5.8/year and 12.4/year, respectively, with Mauritania, Madagascar, Kenya, South Africa, and Sudan having the most human outbreak years. Men had greater odds of RVFV infection than women, and animal contact, butchering, milking, and handling aborted material were significantly associated with greater odds of exposure. Animal infection risk was linked to location, proximity to water, and exposure to other herds or wildlife. RVFV was detected in a variety of mosquito vectors during interepidemic periods, confirming ongoing transmission.

CONCLUSIONS/SIGNIFICANCE

With broad variability in surveillance, case finding, survey design, and RVFV case confirmation, combined with uncertainty about populations-at-risk, there were inconsistent results from location to location. However, it was evident that RVFV transmission is expanding its range and frequency. Gaps assessment indicated the need to harmonize human and animal surveillance and improve diagnostics and genotyping. Given the frequency of RVFV outbreaks, human vaccination has strong potential to mitigate the impact of this now widely endemic disease.

One Health Approach: A Data-Driven Priority for Mitigating Outbreaks of Emerging and Re-Emerging Zoonotic Infectious Diseases

This paper discusses the contributions that One Health principles can make in improving global response to zoonotic infectious disease. We highlight some key benefits of taking a One Health approach to a range of complex infectious disease problems that have defied a more traditional sectoral approach, as well as public health policy and practice, where gaps in surveillance systems need to be addressed. The historical examples demonstrate the scope of One Health, partly from an Australian perspective, but also with an international flavour, and illustrate innovative approaches and outcomes with the types of collaborative partnerships that are required.

Predicting the Geographic Range of an Invasive Livestock Disease across the Contiguous USA under Current and Future Climate Conditions

Vesicular stomatitis (VS) is the most common vesicular livestock disease in North America. Transmitted by direct contact and by several biting insect species, this disease results in quarantines and animal movement restrictions in horses, cattle and swine. As changes in climate drive shifts in geographic distributions of vectors and the viruses they transmit, there is considerable need to improve understanding of relationships among environmental drivers and patterns of disease occurrence. Multidisciplinary approaches integrating pathology, ecology, climatology, and biogeophysics are increasingly relied upon to disentangle complex relationships governing disease. We used a big data model integration approach combined with machine learning to estimate the potential geographic range of VS across the continental United States (CONUS) under long-term mean climate conditions over the past 30 years. The current extent of VS is confined to the western portion of the US and is related to summer and winter precipitation, winter maximum temperature, elevation, fall vegetation biomass, horse density, and proximity to water. Comparison with a climate-only model illustrates the importance of current processes-based parameters and identifies regions where uncertainty is likely to be greatest if mechanistic processes change. We then forecast shifts in the range of VS using climate change projections selected from CMIP5 climate models that most realistically simulate seasonal temperature and precipitation. Climate change scenarios that altered climatic conditions resulted in greater changes to potential range of VS, generally had non-uniform impacts in core areas of the current potential range of VS and expanded the range north and east. We expect that the heterogeneous impacts of climate change across the CONUS will be exacerbated with additional changes in land use and land cover affecting biodiversity and hydrological cycles that are connected to the ecology of insect vectors involved in VS transmission.

Modelling the persistence and control of Rift Valley fever virus in a spatially heterogeneous landscape

The persistence mechanisms of Rift Valley fever (RVF), a zoonotic arboviral haemorrhagic fever, at both local and broader geographical scales have yet to be fully understood and rigorously quantified. We developed a mathematical metapopulation model describing RVF virus transmission in livestock across the four islands of the Comoros archipelago, accounting for island-specific environments and inter-island animal movements. By fitting our model in a Bayesian framework to 2004-2015 surveillance data, we estimated the importance of environmental drivers and animal movements on disease persistence, and tested the impact of different control scenarios on reducing disease burden throughout the archipelago. Here we report that (i) the archipelago network was able to sustain viral transmission in the absence of explicit disease introduction events after early 2007, (ii) repeated outbreaks during 2004-2020 may have gone under-detected by local surveillance, and (iii) co-ordinated within-island control measures are more effective than between-island animal movement restrictions.

The Complex Epidemiological Relationship between Flooding Events and Human Outbreaks of Mosquito-Borne Diseases: A Scoping Review

BACKGROUND

Climate change is expected to increase the frequency of flooding events. Although rainfall is highly correlated with mosquito-borne diseases (MBD) in humans, less research focuses on understanding the impact of flooding events on disease incidence. This lack of research presents a significant gap in climate change-driven disease forecasting.

OBJECTIVES

We conducted a scoping review to assess the strength of evidence regarding the potential relationship between flooding and MBD and to determine knowledge gaps.

METHODS

PubMed, Embase, and Web of Science were searched through 31 December 2020 and supplemented with review of citations in relevant publications. Studies on rainfall were included only if the operationalization allowed for distinction of unusually heavy rainfall events. Data were abstracted by disease (dengue, malaria, or other) and stratified by post-event timing of disease assessment. Studies that conducted statistical testing were summarized in detail.

RESULTS

From 3,008 initial results, we included 131 relevant studies (dengue n = 45 , malaria n = 61 , other MBD n = 49 ). Dengue studies indicated short-term (< 1  month ) decreases and subsequent (1-4 month) increases in incidence. Malaria studies indicated post-event incidence increases, but the results were mixed, and the temporal pattern was less clear. Statistical evidence was limited for other MBD, though findings suggest that human outbreaks of Murray Valley encephalitis, Ross River virus, Barmah Forest virus, Rift Valley fever, and Japanese encephalitis may follow flooding.

DISCUSSION

Flooding is generally associated with increased incidence of MBD, potentially following a brief decrease in incidence for some diseases. Methodological inconsistencies significantly limit direct comparison and generalizability of study results. Regions with established MBD and weather surveillance should be leveraged to conduct multisite research to a) standardize the quantification of relevant flooding, b) study nonlinear relationships between rainfall and disease, c) report outcomes at multiple lag periods, and d) investigate interacting factors that modify the likelihood and severity of outbreaks across different settings. https://doi.org/10.1289/EHP8887.

Scoping future outbreaks: a scoping review on the outbreak prediction of the WHO Blueprint list of priority diseases

BACKGROUND

The WHO's Research and Development Blueprint priority list designates emerging diseases with the potential to generate public health emergencies for which insufficient preventive solutions exist. The list aims to reduce the time to the availability of resources that can avert public health crises. The current SARS-CoV-2 pandemic illustrates that an effective method of mitigating such crises is the pre-emptive prediction of outbreaks. This scoping review thus aimed to map and identify the evidence available to predict future outbreaks of the Blueprint diseases.

METHODS

We conducted a scoping review of PubMed, Embase and Web of Science related to the evidence predicting future outbreaks of Ebola and Marburg virus, Zika virus, Lassa fever, Nipah and Henipaviral disease, Rift Valley fever, Crimean-Congo haemorrhagic fever, Severe acute respiratory syndrome, Middle East respiratory syndrome and Disease X. Prediction methods, outbreak features predicted and implementation of predictions were evaluated. We conducted a narrative and quantitative evidence synthesis to highlight prediction methods that could be further investigated for the prevention of Blueprint diseases and COVID-19 outbreaks.

RESULTS

Out of 3959 articles identified, we included 58 articles based on inclusion criteria. 5 major prediction methods emerged; the most frequent being spatio-temporal risk maps predicting outbreak risk periods and locations through vector and climate data. Stochastic models were predominant. Rift Valley fever was the most predicted disease. Diseases with complex sociocultural factors such as Ebola were often predicted through multifactorial risk-based estimations. 10% of models were implemented by health authorities. No article predicted Disease X outbreaks.

CONCLUSIONS

Spatiotemporal models for diseases with strong climatic and vectorial components, as in River Valley fever prediction, may currently best reduce the time to the availability of resources. A wide literature gap exists in the prediction of zoonoses with complex sociocultural and ecological dynamics such as Ebola, COVID-19 and especially Disease X.

Over 100 Years of Rift Valley Fever: A Patchwork of Data on Pathogen Spread and Spillover

During the past 100 years, Rift Valley fever virus (RVFV), a mosquito-borne virus, has caused potentially lethal disease in livestock, and has been associated with significant economic losses and trade bans. Spillover to humans occurs and can be fatal. Here, we combined data on RVF disease in humans (22 countries) and animals (37 countries) from 1931 to 2020 with seroprevalence studies from 1950 to 2020 (n = 228) from publicly available databases and publications to draw a more complete picture of the past and current RVFV epidemiology. RVFV has spread from its original locus in Kenya throughout Africa and into the Arabian Peninsula. Throughout the study period seroprevalence increased in both humans and animals, suggesting potentially increased RVFV exposure. In 24 countries, animals or humans tested positive for RVFV antibodies even though outbreaks had never been reported there, suggesting RVFV transmission may well go unnoticed. Among ruminants, sheep were the most likely to be exposed during RVF outbreaks, but not during periods of cryptic spread. We discuss critical data gaps and highlight the need for detailed study descriptions, and long-term studies using a one health approach to further convert the patchwork of data to the tale of RFV epidemiology.

Leveraging natural history biorepositories as a global, decentralized, pathogen surveillance network

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic reveals a major gap in global biosecurity infrastructure: a lack of publicly available biological samples representative across space, time, and taxonomic diversity. The shortfall, in this case for vertebrates, prevents accurate and rapid identification and monitoring of emerging pathogens and their reservoir host(s) and precludes extended investigation of ecological, evolutionary, and environmental associations that lead to human infection or spillover. Natural history museum biorepositories form the backbone of a critically needed, decentralized, global network for zoonotic pathogen surveillance, yet this infrastructure remains marginally developed, underutilized, underfunded, and disconnected from public health initiatives. Proactive detection and mitigation for emerging infectious diseases (EIDs) requires expanded biodiversity infrastructure and training (particularly in biodiverse and lower income countries) and new communication pipelines that connect biorepositories and biomedical communities. To this end, we highlight a novel adaptation of Project ECHO’s virtual community of practice model: Museums and Emerging Pathogens in the Americas (MEPA). MEPA is a virtual network aimed at fostering communication, coordination, and collaborative problem-solving among pathogen researchers, public health officials, and biorepositories in the Americas. MEPA now acts as a model of effective international, interdisciplinary collaboration that can and should be replicated in other biodiversity hotspots. We encourage deposition of wildlife specimens and associated data with public biorepositories, regardless of original collection purpose, and urge biorepositories to embrace new specimen sources, types, and uses to maximize strategic growth and utility for EID research. Taxonomically, geographically, and temporally deep biorepository archives serve as the foundation of a proactive and increasingly predictive approach to zoonotic spillover, risk assessment, and threat mitigation.

Rift Valley fever virus detection in susceptible hosts with special emphasis in insects

Rift Valley fever phlebovirus (RVFV, Phenuiviridae) is an emerging arbovirus that can cause potentially fatal disease in many host species including ruminants and humans. Thus, tools to detect this pathogen within tissue samples from routine diagnostic investigations or for research purposes are of major interest. This study compares the immunohistological usefulness of several mono- and polyclonal antibodies against RVFV epitopes in tissue samples derived from natural hosts of epidemiologic importance (sheep), potentially virus transmitting insect species (Culex quinquefasciatus, Aedes aegypti) as well as scientific infection models (mouse, Drosophila melanogaster, C6/36 cell pellet). While the nucleoprotein was the epitope most prominently detected in mammal and mosquito tissue samples, fruit fly tissues showed expression of glycoproteins only. Antibodies against non-structural proteins exhibited single cell reactions in salivary glands of mosquitoes and the C6/36 cell pellet. However, as single antibodies exhibited a cross reactivity of varying degree in non-infected specimens, a careful interpretation of positive reactions and consideration of adequate controls remains of critical importance. The results suggest that primary antibodies directed against viral nucleoproteins and glycoproteins can facilitate RVFV detection in mammals and insects, respectively, and therefore will allow RVFV detection for diagnostic and research purposes.

Quantitative Assessment of the Entry through Mechanical Transport in Aircraft of Rift Valley Fever Virus-Infected Mosquitoes into Previously Unaffected Areas

(1): Rift Valley Fever (RVF) is a zoonotic disease of significant international health concern and considered as an emerging risk to Europe, where no RVF outbreaks in humans or animals have been reported so far. (2): Using a stochastic approach, we estimated the risk of RVF virus (RVFV) introduction during the period of May to October (the period when mosquito populations, including RVFV potential vectors, are present in European countries), into previously unaffected areas (e.g., United Kingdom, UK) via virus-carrying vectors traveling in commercial aircraft from RVF-affected countries (e.g., East Africa); (3): On average N = 68 (95% CI: 0-337), RVF-virus-infected mosquitoes are estimated to be mechanically transported by planes (with N = 0 as most likely), in direct flights from RVF-affected East African countries to the UK, between May and October. This estimate is considered as low but not negligible. The model developed should be easily scaled up to other European countries by amending appropriately country-specific variables (e.g., number of flights between countries) in order to map the areas/airports of higher risk and inform risk management per country accordingly and to adopt risk-mitigation measures.

Potent neutralization of Rift Valley fever virus by human monoclonal antibodies through fusion inhibition

Rift Valley fever virus (RVFV), an emerging arboviral and zoonotic bunyavirus, causes severe disease in livestock and humans. Here, we report the isolation of a panel of monoclonal antibodies (mAbs) from the B cells of immune individuals following natural infection in Kenya or immunization with MP-12 vaccine. The B cell responses of individuals who were vaccinated or naturally infected recognized similar epitopes on both Gc and Gn proteins. The Gn-specific mAbs and two mAbs that do not recognize either monomeric Gc or Gn alone but recognized the hetero-oligomer glycoprotein complex (Gc+Gn) when Gc and Gn were coexpressed exhibited potent neutralizing activities in vitro, while Gc-specific mAbs exhibited relatively lower neutralizing capacity. The two Gc+Gn-specific mAbs and the Gn domain A-specific mAbs inhibited RVFV fusion to cells, suggesting that mAbs can inhibit the exposure of the fusion loop in Gc, a class II fusion protein, and thus prevent fusion by an indirect mechanism without direct fusion loop contact. Competition-binding analysis with coexpressed Gc/Gn and mutagenesis library screening indicated that these mAbs recognize four major antigenic sites, with two sites of vulnerability for neutralization on Gn. In experimental models of infection in mice, representative mAbs recognizing three of the antigenic sites reduced morbidity and mortality when used at a low dose in both prophylactic and therapeutic settings. This study identifies multiple candidate mAbs that may be suitable for use in humans against RVFV infection and highlights fusion inhibition against bunyaviruses as a potential contributor to potent antibody-mediated neutralization.

Laboratory demonstration of the vertical transmission of Rift Valley fever virus by Culex tarsalis mosquitoes

Rift Valley fever virus (RVFV) is a mosquito-transmitted virus with proven ability to emerge into naïve geographic areas. Limited field evidence suggests that RVFV is transmitted vertically from parent mosquito to offspring, but until now this mechanism has not been confirmed in the laboratory. Furthermore, this transmission mechanism has allowed for the prediction of RVFV epizootics based on rainfall patterns collected from satellite information. However, in spite of the relevance to the initiation of epizootic events, laboratory confirmation of vertical transmission has remained an elusive research aim for thirty-five years. Herein we present preliminary evidence of the vertical transmission of RVFV by Culex tarsalis mosquitoes after oral exposure to RVFV. Progeny from three successive gonotrophic cycles were reared to adults, with infectious RVFV confirmed in each developmental stage. Virus was detected in ovarian tissues of parental mosquitoes 7 days after imbibing an infectious bloodmeal. Infection was confirmed in progeny as early as the first gonotrophic cycle, with infection rates ranging from 2.0–10.0%. Virus titers among progeny were low, which may indicate a host mechanism suppressing replication.

Rift Valley fever virus (RVFV) represents a significant threat in terms of its ability to emerge into naïve geographic areas. Furthermore, RVFV represents a global public health risk due to the ability of many mosquito species to transmit the virus and the ease with which the virus can be transported due to increased globalization. The vertical transmission of RVFV by mosquitoes has long been accepted by the research community due to limited field evidence. However, laboratory confirmation of vertical transmission has remained elusive for thirty-five years. We present the first laboratory evidence of vertical transmission of RVFV in the susceptible North American vector, Culex tarsalis. We present two studies that clearly show 1) the accumulation of RVFV antigen in the ovaries of infected mosquitoes and 2) the transmission of RVFV from parent to offspring immediately following an infectious blood meal.

Sero-prevalence of brucellosis, Q-fever and Rift Valley fever in humans and livestock in Somali Region, Ethiopia

Information on zoonotic diseases in humans and livestock are limited in pastoral/agro-pastoral communities in Ethiopia. A multi-stage cross sectional cluster design study was implemented with the aim to establish the seroprevalence of zoonotic diseases including brucellosis, Q-fever and Rift Valley fever (RVF) in humans and livestock in Adadle Woreda of the Somali Region, Ethiopia. Blood samples were collected from humans and livestock and tested by relevant serological tests. For brucellosis, Rose Bengal test (RBT) and indirect ELISA was used for screening and confirmatory diagnosis respectively. Indirect and competitive ELISA were also used for Q-fever and RVF respectively. The individual seropositivity of Q-fever in livestock was 9.6% (95% CI 5.9-15.1) in cattle, 55.7% (95% CI 46.0-65.0) in camels, 48.8% (95% CI 42.5-55.0) in goats, and 28.9% (95% CI 25.0-33.2) in sheep. In humans, seropositivity of Q-fever was 27.0% (95% CI 20.4-34.0), with prevalence in males of 28.9% vs 24.2% in females (OR = 1.3; 95% CI 0.6-2.5). Camel seropositivity of Q-fever was significantly associated with age (OR = 8.1; 95% CI 2.8-23.7). The individual apparent seroprevalence of RVF was 13.2% (95% CI 8.7-18.8) in humans, 17.9% (95% CI 11.0-27.8) in cattle, 42.6% (95% CI 34.8-50.7) in camels, 6.3% (95% CI 3.3-11.6) in goats and 7.4% (95% CI 4.7-11.5) in sheep. Camels had the highest seropositivity of both Q-fever and RVF. Only a weak correlation was observed between human and livestock seropositivity for both Q-fever and RVF. Only cattle and camels were seropositive for brucellosis by iELISA. The individual seroprevalence of brucellosis was 2.8(0.9-6.4) in humans, 1.5% (95% CI 0.2-5.2) in cattle and 0.6% (95% CI 0.0-3.2) in camels. This study showed the importance of zoonoses in Somali Region and is the first published study to describe RVF exposure in humans and livestock in the country. Even though human exposure to RVF virus was reported, public health sector of Somali Region has not given attention to such zoonoses. Collaboration between public and animal health sectors for further investigation on these zoonoses using the One Health concept is indispensable.

Sero-prevalence of West Nile virus and Rift Valley fever virus infections among cattle under extensive production system in South Omo area, southern Ethiopia

West Nile fever (WNF) and Rift Valley fever (RVF) are emerging and re-emerging zoonotic diseases of veterinary and public health importance in Africa. Despite the existence of potential vectors and a wide range of hosts, the transmission of these diseases in domestic animals has not been well documented in the South Omo area of Ethiopia. This study aimed to estimate the sero-prevalence of IgG antibodies produced against West Nile virus (WNV) and Rift Valley fever virus (RVFV) infections among cattle in the South Omo area. Between May and June 2019, blood samples were collected from 397 cattle and screened for IgG antibodies against WNV and RVFV infections using enzyme-linked immunosorbent assay (ELISA). The overall sero-prevalence of IgG antibody to WNV infection was 4.8% (95% CI: 2.67-6.88%), while it was 5.0% to RVFV infection (95% CI: 2.87-7.18). Compared to 1-3 years old cattle, those in the age group ≥ 7 years had significantly higher odds of being positive for WNV (AOR = 6.82; 95% CI: 1.72-26.99) and RVFV (AOR = 4.38; 95% CI: 1.08-17.88) infections. The occurrence of WNV and RVFV infections in cattle population in the present study area indicates the risk of transmission to humans. Strengthening the surveillance system and conducting further studies to identify active cases in domestic and wild animals as well as in humans is crucial to reduce the risk of possible outbreaks.

Multiple impact pathways of the 2015-2016 El Niño in coastal Kenya

The 2015-2016 El Niño had large impacts globally. The effects were not as great as anticipated in Kenya, however, leading some commentators to call it a 'non-event'. Our study uses a novel combination of participatory Climate Vulnerability and Capacity Analysis tools, and new and existing social and biophysical data, to analyse vulnerability to, and the multidimensional impacts of, the 2015-2016 El Niño episode in southern coastal Kenya. Using a social-ecological systems lens and a unique dataset, our study reveals impacts overlooked by conventional analysis. We show how El Niño stressors interact with and amplify existing vulnerabilities to differentially impact local ecosystems and people. The policy significance of this finding is that the development of specific national capacities to deal with El Niño events is insufficient; it will be necessary to also address local vulnerabilities to everyday and recurrent stressors and shocks to build resilience to the effects of El Niño and other extremes in climate and weather.

Invasive Alien Plants in Africa and the Potential Emergence of Mosquito-Borne Arboviral Diseases-A Review and Research Outlook

The emergence of arthropod-borne viruses (arboviruses) as linked to land-use changes, especially the growing agricultural intensification and expansion efforts in rural parts of Africa, is of growing health concern. This places an additional burden on health systems as drugs, vaccines, and effective vector-control measures against arboviruses and their vectors remain lacking. An integrated One Health approach holds potential in the control and prevention of arboviruses. Land-use changes favour invasion by invasive alien plants (IAPs) and investigating their impact on mosquito populations may offer a new dimension to our understanding of arbovirus emergence. Of prime importance to understand is how IAPs influence mosquito life-history traits and how this may affect transmission of arboviruses to mammalian hosts, questions that we are exploring in this review. Potential effects of IAPs may be significant, including supporting the proliferation of immature and adult stages of mosquito vectors, providing additional nutrition and suitable microhabitats, and a possible interaction between ingested secondary plant metabolites and arboviruses. We conclude that aspects of vector biology are differentially affected by individual IAPs and that while some plants may have the potential to indirectly increase the risk of transmission of certain arboviruses by their direct interaction with the vectors, the reverse holds for other IAPs. In addition, we highlight priority research areas to improve our understanding of the potential health impacts of IAPs.

Farm-Level Risk Factors of Increased Abortion and Mortality in Domestic Ruminants during the 2010 Rift Valley Fever Outbreak in Central South Africa

(1) Background: Rift Valley fever (RVF) outbreaks in domestic ruminants have severe socio-economic impacts. Climate-based continental predictions providing early warnings to regions at risk for RVF outbreaks are not of a high enough resolution for ruminant owners to assess their individual risk. (2) Methods: We analyzed risk factors for RVF occurrence and severity at the farm level using the number of domestic ruminant deaths and abortions reported by farmers in central South Africa during the 2010 RVF outbreaks using a Bayesian multinomial hurdle framework. (3) Results: We found strong support that the proportion of days with precipitation, the number of water sources, and the proportion of goats in the herd were positively associated with increased severity of RVF (the numbers of deaths and abortions). We did not find an association between any risk factors and whether RVF was reported on farms. (4) Conclusions: At the farm level we identified risk factors of RVF severity; however, there was little support for risk factors of RVF occurrence. The identification of farm-level risk factors for Rift Valley fever virus (RVFV) occurrence would support and potentially improve current prediction methods and would provide animal owners with critical information needed in order to assess their herd's risk of RVFV infection.

It's risky to wander in September: Modelling the epidemic potential of Rift Valley fever in a Sahelian setting

Estimating the epidemic potential of vector-borne diseases, along with the relative contribution of underlying mechanisms, is crucial for animal and human health worldwide. In West African Sahel, several outbreaks of Rift Valley fever (RVF) have occurred over the last decades, but uncertainty remains about the conditions necessary to trigger these outbreaks. We use the basic reproduction number (R₀) as a measure of RVF epidemic potential in northern Senegal, and map its value in two distinct ecosystems, namely the Ferlo and the Senegal River delta and valley. We consider three consecutive rainy seasons (July-November 2014, 2015 and 2016) and account for several vector and animal species. We parametrize our model with estimates of Aedes vexans arabiensis, Culex poicilipes, Culex tritaeniorhynchus, cattle, sheep and goat abundances. The impact of RVF virus introduction is assessed every week over northern Senegal. We highlight September as the period of highest epidemic potential in northern Senegal, resulting from distinct dynamics in the two study areas. Spatially, in the seasonal environment of the Ferlo, we observe that high-risk locations vary between years. We show that decreased vector densities do not greatly reduce R₀ and that cattle immunity has a greater impact on reducing transmission than small ruminant immunity. The host preferences of vectors and the temperature-dependent time interval between their blood meals are crucial parameters needing further biological investigations.

Development of a multiplex microsphere immunoassay for the detection of antibodies against highly pathogenic viruses in human and animal serum samples

Surveillance of highly pathogenic viruses circulating in both human and animal populations is crucial to unveil endemic infections and potential zoonotic reservoirs. Monitoring the burden of disease by serological assay could be used as an early warning system for imminent outbreaks as an increased seroprevalance often precedes larger outbreaks. However, the multitude of highly pathogenic viruses necessitates the need to identify specific antibodies against several targets from both humans as well as from potential reservoir animals such as bats. In order to address this, we have developed a broadly reactive multiplex microsphere immunoassay (MMIA) for the detection of antibodies against several highly pathogenic viruses from both humans and animals. To this aim, nucleoproteins (NP) of Ebola virus (EBOV), Marburg virus (MARV) and nucleocapsid proteins (NP) of Crimean-Congo haemorrhagic fever virus, Rift Valley fever virus and Dobrava-Belgrade hantavirus were employed in a 5-plex assay for IgG detection. After optimisation, specific binding to each respective NP was shown by testing sera from humans and non-human primates with known infection status. The usefulness of our assay for serosurveillance was shown by determining the immune response against the NP antigens in a panel of 129 human serum samples collected in Guinea between 2011 and 2012 in comparison to a panel of 88 sera from the German blood bank. We found good agreement between our MMIA and commercial or in-house reference methods by ELISA or IIFT with statistically significant higher binding to both EBOV NP and MARV NP coupled microspheres in the Guinea panel. Finally, the MMIA was successfully adapted to detect antibodies from bats that had been inoculated with EBOV- and MARV- virus-like particles, highlighting the versatility of this technique and potentially enabling the monitoring of wildlife as well as human populations with this assay. We were thus able to develop and validate a sensitive and broadly reactive high-throughput serological assay which could be used as a screening tool to detect antibodies against several highly pathogenic viruses.

Transmission of West Nile and five other temperate mosquito-borne viruses peaks at temperatures between 23°C and 26°C

The temperature-dependence of many important mosquito-borne diseases has never been quantified. These relationships are critical for understanding current distributions and predicting future shifts from climate change. We used trait-based models to characterize temperature-dependent transmission of 10 vector-pathogen pairs of mosquitoes (Culex pipiens, Cx. quinquefascsiatus, Cx. tarsalis, and others) and viruses (West Nile, Eastern and Western Equine Encephalitis, St. Louis Encephalitis, Sindbis, and Rift Valley Fever viruses), most with substantial transmission in temperate regions. Transmission is optimized at intermediate temperatures (23-26°C) and often has wider thermal breadths (due to cooler lower thermal limits) compared to pathogens with predominately tropical distributions (in previous studies). The incidence of human West Nile virus cases across US counties responded unimodally to average summer temperature and peaked at 24°C, matching model-predicted optima (24-25°C). Climate warming will likely shift transmission of these diseases, increasing it in cooler locations while decreasing it in warmer locations.

Associations between monthly rainfall and mortality in cattle due to East Coast fever, anaplasmosis and babesiosis

Weather conditions can impact infectious disease transmission, causing mortalities in humans, wild and domestic animals. Although rainfall in dry tropical regions is highly variable over the year, rainfall is thought to play an important role in the transmission of tick-borne diseases. Whether variation in rainfall affects disease-induced mortalities, is, however, poorly understood. Here, we use long-term data on monthly rainfall and Boran cattle mortality (1998-2017) to investigate associations between within-year variation in rainfall and cattle mortalities due to East Coast fever (ECF), anaplasmosis and babesiosis in Laikipia, Kenya, using ARIMAX modelling. Results show a negative correlation between monthly rainfall and cattle mortality for ECF and anaplasmosis, with a lag effect of 2 and 6 months, respectively. There was no association between babesiosis-induced mortalities and monthly rainfall. The results of this study suggest that control of the tick-borne diseases ECF and anaplasmosis to reduce mortalities should be intensified during rainy periods after the respective estimated time lags following dry periods.

Spatial risk analysis for the introduction and circulation of six arboviruses in the Netherlands

Background

Arboviruses are a growing public health concern in Europe, with both endemic and exotic arboviruses expected to spread further into novel areas in the next decades. Predicting where future outbreaks will occur is a major challenge, particularly for regions where these arboviruses are not endemic. Spatial modelling of ecological risk factors for arbovirus circulation can help identify areas of potential emergence. Moreover, combining hazard maps of different arboviruses may facilitate a cost-efficient, targeted multiplex-surveillance strategy in areas where virus transmission is most likely. Here, we developed predictive hazard maps for the introduction and/or establishment of six arboviruses that were previously prioritized for the Netherlands: West Nile virus, Japanese encephalitis virus, Rift Valley fever virus, tick-borne encephalitis virus, louping-ill virus and Crimean-Congo haemorrhagic fever virus.

Methods

Our spatial model included ecological risk factors that were identified as relevant for these arboviruses by an earlier systematic review, including abiotic conditions, vector abundance, and host availability. We used geographic information system (GIS)-based tools and geostatistical analyses to model spatially continuous datasets on these risk factors to identify regions in the Netherlands with suitable ecological conditions for arbovirus introduction and establishment.

Results

The resulting hazard maps show that there is spatial clustering of areas with either a relatively low or relatively high environmental suitability for arbovirus circulation. Moreover, there was some overlap in high-hazard areas for virus introduction and/or establishment, particularly in the southern part of the country.

Conclusions

The similarities in environmental suitability for some of the arboviruses provide opportunities for targeted sampling of vectors and/or sentinel hosts in these potential hotspots of emergence, thereby increasing the efficient use of limited resources for surveillance.

Informing Rift Valley Fever preparedness by mapping seasonally varying environmental suitability

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Database of Rift Valley Fever occurrences from 46 countries over 22 years.

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Predictions of Rift Valley Fever suitability for every month over 1995–2016.

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Identifies areas at-risk by synthesizing time-series of environmental predictions.

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We use human and livestock data to identify possible hotspots of disease spillover.

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We identify places where long-term and routine preparation efforts should be focused.

Background

Rift Valley Fever (RVF) poses a threat to human and animal health throughout much of Africa and the Middle East and has been recognized as a global health security priority and a key preparedness target.

Methods

We combined RVF occurrence data from a systematic literature review with animal notification data from an online database. Using boosted regression trees, we made monthly environmental suitability predictions from January 1995 to December 2016 at a 5 × 5-km resolution throughout regions of Africa, Europe, and the Middle East. We calculated the average number of months per year suitable for transmission, the mean suitability for each calendar month, and the “spillover potential,” a measure incorporating suitability with human and livestock populations.

Results

Several countries where cases have not yet been reported are suitable for RVF. Areas across the region of interest are suitable for transmission at different times of the year, and some areas are suitable for multiple seasons each year. Spillover potential results show areas within countries where high populations of humans and livestock are at risk for much of the year.

Conclusions

The widespread environmental suitability of RVF highlights the need for increased preparedness, even in countries that have not previously experienced cases. These maps can aid in prioritizing long-term RVF preparedness activities and determining optimal times for recurring preparedness activities. Given an outbreak, our results can highlight areas often at risk for subsequent transmission that month, enabling decision-makers to target responses effectively.

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.

Rift Valley Fever: Important Considerations for Risk Mitigation and Future Outbreaks

Rift Valley fever virus (RVFV) is a zoonotic phlebovirus of the Phenuiviridae family with great opportunity for emergence in previously unaffected regions, despite its current geographical limits. Outbreaks of RVFV often infect humans or domesticated animals, such as livestock, concurrently and occur sporadically, ranging from localized outbreaks in villages to multi-country events that spread rapidly. The true burden of Rift Valley fever (RVF) is not well defined due to underreporting, misdiagnosis caused by the broad spectrum of disease presentation, and minimal access for rapid and accurate laboratory confirmation. Severe symptoms may include hemorrhagic fever, loss of vision, psychological impairment or disturbances, and organ failure. Those living in endemic areas and travelers should be aware of the potential for exposure to ongoing outbreaks or interepidemic transmission, and engage in behaviors to minimize exposure risks, as vaccinations in humans are currently unavailable and animal vaccinations are not used routinely or ubiquitously. The lack of vaccines approved for use in humans is concerning, as RVFV has proven to be highly pathogenic in naïve populations, causing severe disease in a large percent of confirmed cases, which could have considerable impact on human health.

Using models to provide rapid programme support for California's efforts to suppress Huanglongbing disease of citrus

We describe a series of operational questions posed during the state-wide response in California to the arrival of the invasive citrus disease Huanglongbing. The response is coordinated by an elected committee from the citrus industry and operates in collaboration with the California Department of Food and Agriculture, which gives it regulatory authority to enforce the removal of infected trees. The paper reviews how surveillance for disease and resource allocation between detection and delimitation have been addressed, based on epidemiological principles. In addition, we describe how epidemiological analyses have been used to support rule-making to enact costly but beneficial regulations and we highlight two recurring themes in the programme support work: (i) data are often insufficient for quantitative analyses of questions and (ii) modellers and decision-makers alike may be forced to accept the need to make decisions on the basis of simple or incomplete analyses that are subject to considerable uncertainty. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.

Relative Distribution, Diversity, and Bloodmeal Sources of Mosquitoes and Known Vectors of Rift Valley Fever Phlebovirus in Three Differing Ecosystems in Bura, Tana River County, Kenya

Environmental modifications disturb the equilibrium of mosquito populations, altering the risk of mosquito-borne diseases. Mosquito distribution, diversity, and bloodmeal sources were examined to compare Rift Valley fever (RVF) risk among irrigated, riverine, and pastoral ecosystems in Bura, Tana River County, Kenya, between September 2014 and June 2015. Thirty-eight households and 21 irrigation fields were selected for the study. Mosquitoes were trapped with carbon dioxide-impregnated CDC traps, one trap per household and three traps per irrigated field, and morphologically identified using taxonomic keys. Host DNA was extracted from engorged females and cytochrome b genes amplified by PCR to identify sources of bloodmeals. A total of 21,015 mosquitoes were collected; 5742 within households in the 3 ecosystems and 15,273 within irrigated fields. Mosquitoes collected within irrigated fields belonged to 8 genera and 37 species, while those from households within the irrigation scheme belonged to 6 genera and 29 species. Collections from riverine and pastoral households belonged to five and four genera, respectively. The most abundant genera in the irrigated fields were Aedes (21%) and Mansonia (22%), while Anopheles (43%) was the most abundant within households. Most mosquitoes in riverine and pastoral households belonged to Anopheles (76%) and Aedes (65%) genera, respectively. Seasonal variation driven by rainfall was evidenced by spikes in mosquito numbers within irrigated and riverine ecosystems. Host species identification revealed that goats and humans were the main sources of bloodmeal. There was an overall increase in mosquito abundance and diversity as a result of the presence of the irrigated ecosystem in this county, and an increased availability of highly RVF-susceptible hosts as a result of the establishment and concentration of residential areas, promoting potential vector-host contacts. These results highlight the impact of anthropogenic changes on mosquito ecology, potentially heightening the risk of transmission and maintenance of RVF in this region.

Integrated Early Warning Surveillance: Achilles' Heel of One Health?

Emerging and re-emerging infectious diseases and zoonoses indicate the importance of the One Health (OH) approach for early warning. At present, even when surveillance data are available, they are infrequently timeously shared between the health sectors. In the context of the MediLabSecure (MLS) Project, we investigated the collection of a set of surveillance indicators able to provide data for the implementation of integrated early warning systems in the 22 MLS countries of the Mediterranean, Black Sea and Sahel regions. We used an online questionnaire (covering vector, human, and animal sectors), focusing on seven relevant arboviruses, that was submitted to 110 officially appointed experts. Results showed that West Nile virus was perceived as the most relevant zoonotic pathogen, while Dengue virus was the most relevant non-zoonotic pathogen in the study area. Data collection of early warning indicators is in place at a different level for all the investigated pathogens and in almost all the MLS Countries. Further assessments on the reliability of the collection in place and on the feasibility of piloting an integrated early warning system for arbovirus could verify if integrated early warning really represents the Achilles' heel of OH.

Implementing One Health approaches to confront emerging and re-emerging zoonotic disease threats: lessons from PREDICT

Recurring outbreaks of emerging and re-emerging zoonoses, such as Ebola virus disease, avian influenza, and Nipah virus, serve as a reminder that the health of humans, animals, and the environment are interconnected and that early response to emerging zoonotic pathogens requires a coordinated, interdisciplinary, cross-sectoral approach. As our world becomes increasingly connected, emerging diseases pose a greater threat, requiring coordination at local, regional, and global levels. One Health is a multisectoral, transdisciplinary, and collaborative approach promoted to more effectively address these complex health threats. Despite strong advocacy for One Health, challenges for practical implementation remain. Here we discuss the value of the One Health approach for addressing global health challenges. We also share strategies applied to achieve successful outcomes through the USAID Emerging Pandemic Threats Program PREDICT project, which serve as useful case studies for implementing One Health approaches. Lastly, we explore methods for promoting more formal One Health implementation to capitalize on the added value of shared knowledge and leveraged resources.

Predicting Abundances of Aedes mcintoshi, a primary Rift Valley fever virus mosquito vector

Rift Valley fever virus (RVFV) is a mosquito-borne zoonotic arbovirus with important livestock and human health, and economic consequences across Africa and the Arabian Peninsula. Climate and vegetation monitoring guide RVFV forecasting models and early warning systems; however, these approaches make monthly predictions and a need exists to predict primary vector abundances at finer temporal scales. In Kenya, an important primary RVFV vector is the mosquito Aedes mcintoshi. We used a zero-inflated negative binomial regression and multimodel averaging approach with georeferenced Ae. mcintoshi mosquito counts and remotely sensed climate and topographic variables to predict where and when abundances would be high in Kenya and western Somalia. The data supported a positive effect on abundance of minimum wetness index values within 500 m of a sampling site, cumulative precipitation values 0 to 14 days prior to sampling, and elevated land surface temperature values ~3 weeks prior to sampling. The probability of structural zero counts of mosquitoes increased as percentage clay in the soil decreased. Weekly retrospective predictions for unsampled locations across the study area between 1 September and 25 January from 2002 to 2016 predicted high abundances prior to RVFV outbreaks in multiple foci during the 2006-2007 epizootic, except for two districts in Kenya. Additionally, model predictions supported the possibility of high Ae. mcintoshi abundances in Somalia, independent of Kenya. Model-predicted abundances were low during the 2015-2016 period when documented outbreaks did not occur, although several surveillance systems issued warnings. Model predictions prior to the 2018 RVFV outbreak indicated elevated abundances in Wajir County, Kenya, along the border with Somalia, but RVFV activity occurred west of the focus of predicted high Ae. mcintoshi abundances.