Building resilience to mosquito-borne diseases in the Caribbean.

Small island developing states in the Caribbean are among the most vulnerable countries on the planet to climate variability and climate change. In the last 3 decades, the Caribbean region has undergone frequent and intense heat waves, storms, floods, and droughts. This has had a detrimental impact on population health and well-being, including an increase in infectious disease outbreaks. Recent advances in climate science have enhanced our ability to anticipate hydrometeorological hazards and associated public health challenges. Here, we discuss progress towards bridging the gap between climate science and public health decision-making in the Caribbean to build health system resilience to extreme climatic events. We focus on the development of climate services to help manage mosquito-transmitted disease epidemics. There are numerous areas of ongoing biological research aimed at better understanding the direct and indirect impacts of climate change on the transmission of mosquito-borne diseases. Here, we emphasise additional factors that affect our ability to operationalise this biological understanding. We highlight a lack of financial resources, technical expertise, data sharing, and formalised partnerships between climate and health communities as major limiting factors to developing sustainable climate services for health. Recommendations include investing in integrated climate, health and mosquito surveillance systems, building regional and local human resource capacities, and designing national and regional cross-sectoral policies and national action plans. This will contribute towards achieving the Sustainable Development Goals (SDGs) and maximising regional development partnerships and co-benefits for improved health and well-being in the Caribbean.

Mapping current and future thermal limits to suitability for malaria transmission by the invasive mosquito Anopheles stephensi.

BACKGROUND: Anopheles stephensi is a malaria-transmitting mosquito that has recently expanded from its primary range in Asia and the Middle East, to locations in Africa. This species is a competent vector of both Plasmodium falciparum and Plasmodium vivax malaria. Perhaps most alarming, the characteristics of An. stephensi, such as container breeding and anthropophily, make it particularly adept at exploiting built environments in areas with no prior history of malaria risk. METHODS: In this paper, global maps of thermal transmission suitability and people at risk (PAR) for malaria transmission by An. stephensi were created, under current and future climate. Temperature-dependent transmission suitability thresholds derived from recently published species-specific thermal curves were used to threshold gridded, monthly mean temperatures under current and future climatic conditions. These temperature driven transmission models were coupled with gridded population data for 2020 and 2050, under climate-matched scenarios for future outcomes, to compare with baseline predictions for 2020 populations. RESULTS: Using the Global Burden of Disease regions approach revealed that heterogenous regional increases and decreases in risk did not mask the overall pattern of massive increases of PAR for malaria transmission suitability with An. stephensi presence. General patterns of poleward expansion for thermal suitability were seen for both P. falciparum and P. vivax transmission potential. CONCLUSIONS: Understanding the potential suitability for An. stephensi transmission in a changing climate provides a key tool for planning, given an ongoing invasion and expansion of the vector. Anticipating the potential impact of onward expansion to transmission suitable areas, and the size of population at risk under future climate scenarios, and where they occur, can serve as a large-scale call for attention, planning, and monitoring.

A systematic review of the data, methods and environmental covariates used to map Aedes-borne arbovirus transmission risk.

BACKGROUND: Aedes (Stegomyia)-borne diseases are an expanding global threat, but gaps in surveillance make comprehensive and comparable risk assessments challenging. Geostatistical models combine data from multiple locations and use links with environmental and socioeconomic factors to make predictive risk maps. Here we systematically review past approaches to map risk for different Aedes-borne arboviruses from local to global scales, identifying differences and similarities in the data types, covariates, and modelling approaches used. METHODS: We searched on-line databases for predictive risk mapping studies for dengue, Zika, chikungunya, and yellow fever with no geographical or date restrictions. We included studies that needed to parameterise or fit their model to real-world epidemiological data and make predictions to new spatial locations of some measure of population-level risk of viral transmission (e.g. incidence, occurrence, suitability, etc.). RESULTS: We found a growing number of arbovirus risk mapping studies across all endemic regions and arboviral diseases, with a total of 176 papers published 2002-2022 with the largest increases shortly following major epidemics. Three dominant use cases emerged: (i) global maps to identify limits of transmission, estimate burden and assess impacts of future global change, (ii) regional models used to predict the spread of major epidemics between countries and (iii) national and sub-national models that use local datasets to better understand transmission dynamics to improve outbreak detection and response. Temperature and rainfall were the most popular choice of covariates (included in 50% and 40% of studies respectively) but variables such as human mobility are increasingly being included. Surprisingly, few studies (22%, 31/144) robustly tested combinations of covariates from different domains (e.g. climatic, sociodemographic, ecological, etc.) and only 49% of studies assessed predictive performance via out-of-sample validation procedures. CONCLUSIONS: Here we show that approaches to map risk for different arboviruses have diversified in response to changing use cases, epidemiology and data availability. We identify key differences in mapping approaches between different arboviral diseases, discuss future research needs and outline specific recommendations for future arbovirus mapping.

Assessing the risk of human-to-wildlife pathogen transmission for conservation and public health.

The SARS-CoV-2 pandemic has led to increased concern over transmission of pathogens from humans to animals, and its potential to threaten conservation and public health. To assess this threat, we reviewed published evidence of human-to-wildlife transmission events, with a focus on how such events could threaten animal and human health. We identified 97 verified examples, involving a wide range of pathogens; however, reported hosts were mostly non-human primates or large, long-lived captive animals. Relatively few documented examples resulted in morbidity and mortality, and very few led to maintenance of a human pathogen in a new reservoir or subsequent "secondary spillover" back into humans. We discuss limitations in the literature surrounding these phenomena, including strong evidence of sampling bias towards non-human primates and human-proximate mammals and the possibility of systematic bias against reporting human parasites in wildlife, both of which limit our ability to assess the risk of human-to-wildlife pathogen transmission. We outline how researchers can collect experimental and observational evidence that will expand our capacity for risk assessment for human-to-wildlife pathogen transmission.

Malaria transmission in Nepal under climate change: anticipated shifts in extent and season, and comparison with risk definitions for intervention.

BACKGROUND: Climate and climate change affect the spatial pattern and seasonality of malaria risk. Season lengths and spatial extents of mapped current and future malaria transmission suitability predictions for Nepal were assessed for a combination of malaria vector and parasites: Anopheles stephensi and Plasmodium falciparum (ASPF) and An. stephensi and Plasmodium vivax (ASPV) and compared with observed estimates of malaria risk in Nepal. METHODS: Thermal bounds of malaria transmission suitability for baseline (1960-1990) and future climate projections (RCP 4.5 and RCP 8.5 in 2030 and 2050) were extracted from global climate models and mapped for Nepal. Season length and spatial extent of suitability between baseline and future climate scenarios for ASPF and ASPV were compared using the Warren's I metric. Official 2010 DoHS risk districts (DRDs) and 2021 DoHS risk wards (DRWs), and spatiotemporal incidence trend clusters (ITCs) were overlaid on suitability season length and extent maps to assess agreement, and potential mismatches. RESULTS: Shifts in season length and extent of malaria transmission suitability in Nepal are anticipated under both RCP 4.5 and RCP 8.5 scenarios in 2030 and 2050, compared to baseline climate. The changes are broadly consistent across both future climate scenarios for ASPF and ASPV. There will be emergence of suitability and increasing length of season for both ASPF and ASPV and decreasing length of season for ASPV by 2050. The emergence of suitability will occur in low and no-risk DRDs and outside of high and moderate-risk DRWs, season length increase will occur across all DRD categories, and outside of high and moderate-risk DRWs. The high and moderate risk DRWs of 2021 fall into ITCs with decreasing trend. CONCLUSIONS: The study identified areas of Nepal where malaria transmission suitability will emerge, disappear, increase, and decrease in the future. However, most of these areas are anticipated outside of the government's current and previously designated high and moderate-risk areas, and thus outside the focus of vector control interventions. Public health officials could use these anticipated changing areas of malaria risk to inform vector control interventions for eliminating malaria from the country, and to prevent malaria resurgence.

Mammal virus diversity estimates are unstable due to accelerating discovery effort.

Host-virus association data underpin research into the distribution and eco-evolutionary correlates of viral diversity and zoonotic risk across host species. However, current knowledge of the wildlife virome is inherently constrained by historical discovery effort, and there are concerns that the reliability of ecological inference from host-virus data may be undermined by taxonomic and geographical sampling biases. Here, we evaluate whether current estimates of host-level viral diversity in wild mammals are stable enough to be considered biologically meaningful, by analysing a comprehensive dataset of discovery dates of 6571 unique mammal host-virus associations between 1930 and 2018. We show that virus discovery rates in mammal hosts are either constant or accelerating, with little evidence of declines towards viral richness asymptotes, even in highly sampled hosts. Consequently, inference of relative viral richness across host species has been unstable over time, particularly in bats, where intensified surveillance since the early 2000s caused a rapid rearrangement of species' ranked viral richness. Our results illustrate that comparative inference of host-level virus diversity across mammals is highly sensitive to even short-term changes in sampling effort. We advise caution to avoid overinterpreting patterns in current data, since it is feasible that an analysis conducted today could draw quite different conclusions than one conducted only a decade ago.

HIV-Related Stigma Moderates the Relation Between Perceived Susceptibility and HIV Testing Intention Among Heterosexual (but Not Sexual Minority) College Students.

HIV-related stigma remains a considerable barrier to engaging at-risk populations in HIV testing and prevention programs. We assessed the moderating role of HIV-related stigma on the relation between perceived susceptibility to HIV and HIV testing intention among college students. We hypothesized that the moderating role of HIV-related stigma would be differential between heterosexual and sexual minority college students. We administered a survey focused on HIV-related knowledge, attitudes, and behaviors in spring 2016 (N = 2,159). We used multigroup path analysis to analyze the hypothesized moderation. HIV-related stigma moderated the relation between perceived susceptibility and testing intention for heterosexual but not sexual minority college students. Specifically, higher HIV-related stigma decreased the association between perceived susceptibility and testing intention. These results demonstrate the importance of priority population segmentation for HIV testing campaigns.

Warming temperatures could expose more than 1.3 billion new people to Zika virus risk by 2050.

In the aftermath of the 2015 pandemic of Zika virus (ZIKV), concerns over links between climate change and emerging arboviruses have become more pressing. Given the potential that much of the world might remain at risk from the virus, we used a previously established temperature-dependent transmission model for ZIKV to project climate change impacts on transmission suitability risk by mid-century (a generation into the future). Based on these model predictions, in the worst-case scenario, over 1.3 billion new people could face suitable transmission temperatures for ZIKV by 2050. The next generation will face substantially increased ZIKV transmission temperature suitability in North America and Europe, where naïve populations might be particularly vulnerable. Mitigating climate change even to moderate emissions scenarios could significantly reduce global expansion of climates suitable for ZIKV transmission, potentially protecting around 200 million people. Given these suitability risk projections, we suggest an increased priority on research establishing the immune history of vulnerable populations, modeling when and where the next ZIKV outbreak might occur, evaluating the efficacy of conventional and novel intervention measures, and increasing surveillance efforts to prevent further expansion of ZIKV.

Are malaria transmission-blocking vaccines acceptable to high burden communities? Results from a mixed methods study in Bo, Sierra Leone.

BACKGROUND: Malaria transmission-blocking vaccines (TBVs) could help break the cycle of malaria transmission by conferring community rather than individual protection. When introducing new intervention strategies, uptake is dependent on acceptability, not just efficacy. In this exploratory study on acceptability of TBVs in Sierra Leone, it was hypothesized that TBVs would be largely acceptable to adults and health workers in areas with relatively few ongoing malaria interventions, and that (i) knowledge of malaria and vaccines, (ii) health behaviours associated with malaria and vaccines, and (iii) attitudes towards different vaccines types could lead to greater TBV acceptability. METHODS: This study used a mixed methods approach in Bo, Sierra Leone, to understand community knowledge, attitudes, and practices related to malaria and vaccination in general. This included: (i) a population-based cross-sectional survey (n=615 adults), (ii) 6 focus group discussions with parents, and (iii) 20 key informant interviews. The concept of a TBV was explained to participants before they were asked about their willingness to accept this vaccine modality as part of an integrated malaria elimination programme. RESULTS: This study found that most adults would be willing to receive a TBV vaccine. Respondents noted mostly positive past experiences with adult and childhood vaccinations for other infectious diseases and high levels of engagement in other malaria prevention behaviors such as bed nets. Perceived barriers to TBV acceptance were largely focused on general community-level distribution of a vaccine, including personal fears of vaccination and possible costs. After an explanation of the TBV mechanism, nearly all focus group and interview participants believed that community members would accept the vaccine as part of an integrated malaria control approach. Both parents and health workers offered insight on how to successfully roll-out a future TBV vaccination programme. CONCLUSIONS: The willingness of community members in Bo, Sierra Leone to accept a TBV as part of an integrated anti-malarial strategy suggests that the atypical mechanism of TBV action might not be an obstacle to future clinical trials. This study's findings suggests that perceived general barriers to vaccination implementation, such as perceived personal fears and vaccine cost, must be addressed in future clinical and implementation research studies.

Sex-Specific Elk Resource Selection during the Anthrax Risk Period.

Anthrax, caused by the spore-forming bacterium Bacillus anthracis, is a zoonosis affecting animals and humans globally. In the United States, anthrax outbreaks occur in wildlife and livestock, with frequent outbreaks in native and exotic wildlife species in Texas, livestock outbreaks in the Dakotas, and sporadic mixed outbreaks in Montana. Understanding where pathogen and host habitat selection overlap is essential for anthrax management. Resource selection and habitat use of ungulates may be sex-specific and lead to differential anthrax exposure risks across the landscape for males and females. We evaluated female elk (Cervus canadensis) resource selection in the same study areas as male elk in a previous anthrax risk study to identify risk of anthrax transmission to females and compare transmission risk between females and males. We developed a generalized linear mixed-effect model to estimate resource selection for female elk in southwest Montana during the June to August anthrax transmission risk period. We then predicted habitat selection of female and male elk across the study area and compared selection with the distribution of anthrax risk to identify spatial distributions of potential anthrax exposure for the male and female elk. Female and male elk selected different resources during the anthrax risk period, which resulted in different anthrax exposure areas for females and males. The sex-specific resource selection and habitat use could infer different areas of risk for anthrax transmission, which can improve anthrax and wildlife management and have important public health and economic implications.

A generic arboviral model framework for exploring trade-offs between vector control and environmental concerns.

Effective public health measures must balance potentially conflicting demands from populations they serve. In the case of infectious disease risks from mosquito-borne infections, such as Zika virus, public concern about the pathogen may be counterbalanced by public concern about environmental contamination from chemical agents used for vector control. Here we introduce a generic framework for modeling how the spread of an infectious pathogen might lead to varying public perceptions, and therefore tolerance, of both disease risk and pesticide use. We consider how these dynamics might impact the spread of a vector-borne disease. We tailor and parameterize our model for direct application to Zika virus as spread by Aedes aegypti mosquitoes, though the framework itself has broad applicability to any arboviral infection. We demonstrate how public risk perception of both disease and pesticides may drastically impact the spread of a mosquito-borne disease in a susceptible population. We conclude that models hoping to inform public health decision making about how best to mitigate arboviral disease risks should explicitly consider the potential public demand for, or rejection of, chemical control of mosquito populations.

Shifting transmission risk for malaria in Africa with climate change: a framework for planning and intervention.

BACKGROUND: Malaria continues to be a disease of massive burden in Africa, and the public health resources targeted at surveillance, prevention, control, and intervention comprise large outlays of expense. Malaria transmission is largely constrained by the suitability of the climate for Anopheles mosquitoes and Plasmodium parasite development. Thus, as climate changes, shifts in geographic locations suitable for transmission, and differing lengths of seasons of suitability will occur, which will require changes in the types and amounts of resources. METHODS: The shifting geographic risk of malaria transmission was mapped, in context of changing seasonality (i.e. endemic to epidemic, and vice versa), and the number of people affected. A published temperature-dependent model of malaria transmission suitability was applied to continental gridded climate data for multiple future AR5 climate model projections. The resulting outcomes were aligned with programmatic needs to provide summaries at national and regional scales for the African continent. Model outcomes were combined with population projections to estimate the population at risk at three points in the future, 2030, 2050, and 2080, under two scenarios of greenhouse gas emissions (RCP4.5 and RCP8.5). RESULTS: Estimated geographic shifts in endemic and seasonal suitability for malaria transmission were observed across all future scenarios of climate change. The worst-case regional scenario (RCP8.5) of climate change predicted an additional 75.9 million people at risk from endemic (10-12 months) exposure to malaria transmission in Eastern and Southern Africa by the year 2080, with the greatest population at risk in Eastern Africa. Despite a predominance of reduction in season length, a net gain of 51.3 million additional people is predicted be put at some level of risk in Western Africa by midcentury. CONCLUSIONS: This study provides an updated view of potential malaria geographic shifts in Africa under climate change for the more recent climate model projections (AR5), and a tool for aligning findings with programmatic needs at key scales for decision-makers. In describing shifting seasonality, it was possible to capture transitions between endemic and epidemic risk areas, to facilitate the planning for interventions aimed at year-round risk versus anticipatory surveillance and rapid response to potential outbreak locations.

Comparing prioritization strategies for delivering indoor residual spray (IRS) implementation, using a network approach.

BACKGROUND: Indoor residual spraying (IRS) is an effective method to control malaria-transmitting Anopheles mosquitoes and often complements insecticide-treated mosquito nets, the predominant malaria vector control intervention. With insufficient funds to cover every household, malaria control programs must balance the malaria risk to a particular human community against the financial cost of spraying that community. This study creates a framework for modelling the distance to households for targeting IRS implementation, and applies it to potential risk prioritization strategies in four provinces (Luapula, Muchinga, Eastern, and Northern) in Zambia. METHODS: Optimal network models were used to assess the travel distance of routes between operations bases and human communities identified through remote sensing. Network travel distances were compared to Euclidean distances, to demonstrate the importance of accounting for road routes. The distance to reaching communities for different risk prioritization strategies were then compared assuming sufficient funds to spray 50% of households, using four underlying malarial risk maps: (a) predicted Plasmodium falciparum parasite rate in 2-10 years olds (PfPR), or (b) predicted probability of the presence of each of three main malaria transmitting anopheline vectors (Anopheles arabiensis, Anopheles funestus, Anopheles gambiae). RESULTS: The estimated one-way network route distance to reach communities to deliver IRS ranged from 0.05 to 115.69 km. Euclidean distance over and under-estimated these routes by - 101.21 to 41.79 km per trip, as compared to the network route method. There was little overlap between risk map prioritization strategies, both at a district-by-district scale, and across all four provinces. At both scales, agreement for inclusion or exclusion from IRS across all four prioritization strategies occurred in less than 10% of houses. The distances to reaching prioritized communities were either lower, or not statistically different from non-prioritized communities, at both scales of strategy. CONCLUSION: Variation in distance to targeted communities differed depending on risk prioritization strategy used, and higher risk prioritization did not necessarily translate into greater distances in reaching a human community. These findings from Zambia suggest that areas with higher malaria burden may not necessarily be more remote than areas with lower malaria burden.

A network analysis framework to improve the delivery of mosquito abatement services in Machala, Ecuador.

BACKGROUND: Vector-borne disease places a high health and economic burden in the American tropics. Comprehensive vector control programs remain the primary method of containing local outbreaks. With limited resources, many vector control operations struggle to serve all affected communities within their districts. In the coastal city of Machala, Ecuador, vector control services, such as application of larvicides and truck-mounted fogging, are delivered through two deployment facilities managed by the Ecuadorian Ministry of Health. Public health professionals in Machala face several logistical issues when delivering mosquito abatement services, namely applying limited resources in ways that will most effectively suppress vectors of malaria, dengue, and encephalitis viruses. METHODS: Using a transportation network analysis framework, we built models of service areas and optimized delivery routes based on distance costs associated with accessing neighborhoods throughout the city. Optimized routes were used to estimate the relative cost of accessing neighborhoods for mosquito control services in Machala, creating a visual tool to guide decision makers and maximize mosquito control program efficiency. Location-allocation analyses were performed to evaluate efficiency gains of moving service deployment to other available locations with respect to distance to service hub, neighborhood population, dengue incidence, and housing condition. RESULTS: Using this framework, we identified different locations for targeting mosquito control efforts, dependent upon management goals and specified risk factors of interest, including human population, housing condition, and reported dengue incidence. Our models indicate that neighborhoods on the periphery of Machala with the poorest housing conditions are the most costly to access. Optimal locations of facilities for deployment of control services change depending on pre-determined management priorities, increasing the population served via inexpensive routes up to 34.9%, and reducing overall cost of accessing neighborhoods up to 12.7%. CONCLUSIONS: Our transportation network models indicate that current locations of mosquito control facilities in Machala are not ideal for minimizing driving distances or maximizing populations served. Services may be optimized by moving vector control operations to other existing public health facilities in Machala. This work represents a first step in creating a spatial tool for planning and critically evaluating the systematic delivery of mosquito control services in Machala and elsewhere.

Thermal biology of mosquito-borne disease.

Mosquito-borne diseases cause a major burden of disease worldwide. The vital rates of these ectothermic vectors and parasites respond strongly and nonlinearly to temperature and therefore to climate change. Here, we review how trait-based approaches can synthesise and mechanistically predict the temperature dependence of transmission across vectors, pathogens, and environments. We present 11 pathogens transmitted by 15 different mosquito species - including globally important diseases like malaria, dengue, and Zika - synthesised from previously published studies. Transmission varied strongly and unimodally with temperature, peaking at 23-29ºC and declining to zero below 9-23ºC and above 32-38ºC. Different traits restricted transmission at low versus high temperatures, and temperature effects on transmission varied by both mosquito and parasite species. Temperate pathogens exhibit broader thermal ranges and cooler thermal minima and optima than tropical pathogens. Among tropical pathogens, malaria and Ross River virus had lower thermal optima (25-26ºC) while dengue and Zika viruses had the highest (29ºC) thermal optima. We expect warming to increase transmission below thermal optima but decrease transmission above optima. Key directions for future work include linking mechanistic models to field transmission, combining temperature effects with control measures, incorporating trait variation and temperature variation, and investigating climate adaptation and migration.

Effects of Political Instability in Venezuela on Malaria Resurgence at Ecuador-Peru Border, 2018.

Mass migration from Venezuela has increased malaria resurgence risk across South America. During 2018, migrants from Venezuela constituted 96% of imported malaria cases along the Ecuador-Peru border. Plasmodium vivax predominated (96%). Autochthonous malaria cases emerged in areas previously malaria-free. Heightened malaria control and a response to this humanitarian crisis are imperative.

Sexual Risk Factors and Human Immunodeficiency Virus Testing Intention Among At-Risk College Students Who Have Never Been Tested.

Survey data from a university in the southeast United States were used to estimate the relation between sexual risk factors, perceived susceptibility, and human immunodeficiency virus testing intention among sexually active college students who had never been tested. Sexual risk factors, but not knowledge, were indirectly related to increased human immunodeficiency virus testing intention through perceived susceptibility.

Gastrointestinal parasites of the New England cottontail rabbit (Sylvilagus transitionalis) and eastern cottontail rabbit (Sylvilagus floridanus) in the Hudson Valley, New York.

The New England cottontail rabbit (NEC, Sylvilagus transitionalis) population has decreased dramatically in New York, USA, and the role of parasites in limiting the population has never been examined. The closely related and sympatric eastern cottontail rabbit (EC, Sylvilagus floridanus) was introduced into the range of NEC by humans and is currently thriving. This study aimed to investigate gastrointestinal parasites of the NEC and the EC and compare their parasite communities. Fecal pellets from 195 NEC and 125 EC were collected from the Hudson Valley, New York, in the winter of 2013-2014. Centrifugal fecal floats were performed in Sheather's sugar solution, and parasite ova and cysts were examined microscopically to identify gastrointestinal parasites present. For all pellets combined (n = 320), 91% were found to harbor at least 1 parasite species, with Eimeria species being the most common. Genetic analysis of pellets using microsatellite DNA identified 248 individual rabbits, with parasite prevalence (94%) similar to the prevalence estimate based on all pellets (91%). EC samples had a significantly higher (p < 0.05) parasite species richness (1.73, range 0-4) than NEC (1.20, range 0-3). EC and NEC shared 3 moderate to high (9-89%) prevalence parasites, in which EC prevalence was consistently higher. One parasite species was only found in NEC, and two were only found in EC, but the majority of these were of low abundance, precluding further statistical analyses.

Making ecological models adequate.

Critical evaluation of the adequacy of ecological models is urgently needed to enhance their utility in developing theory and enabling environmental managers and policymakers to make informed decisions. Poorly supported management can have detrimental, costly or irreversible impacts on the environment and society. Here, we examine common issues in ecological modelling and suggest criteria for improving modelling frameworks. An appropriate level of process description is crucial to constructing the best possible model, given the available data and understanding of ecological structures. Model details unsupported by data typically lead to over parameterisation and poor model performance. Conversely, a lack of mechanistic details may limit a model's ability to predict ecological systems' responses to management. Ecological studies that employ models should follow a set of model adequacy assessment protocols that include: asking a series of critical questions regarding state and control variable selection, the determinacy of data, and the sensitivity and validity of analyses. We also need to improve model elaboration, refinement and coarse graining procedures to better understand the relevancy and adequacy of our models and the role they play in advancing theory, improving hind and forecasting, and enabling problem solving and management.

Nonlinear and delayed impacts of climate on dengue risk in Barbados: A modelling study.

BACKGROUND: Over the last 5 years (2013-2017), the Caribbean region has faced an unprecedented crisis of co-occurring epidemics of febrile illness due to arboviruses transmitted by the Aedes sp. mosquito (dengue, chikungunya, and Zika). Since 2013, the Caribbean island of Barbados has experienced 3 dengue outbreaks, 1 chikungunya outbreak, and 1 Zika fever outbreak. Prior studies have demonstrated that climate variability influences arbovirus transmission and vector population dynamics in the region, indicating the potential to develop public health interventions using climate information. The aim of this study is to quantify the nonlinear and delayed effects of climate indicators, such as drought and extreme rainfall, on dengue risk in Barbados from 1999 to 2016. METHODS AND FINDINGS: Distributed lag nonlinear models (DLNMs) coupled with a hierarchal mixed-model framework were used to understand the exposure-lag-response association between dengue relative risk and key climate indicators, including the standardised precipitation index (SPI) and minimum temperature (Tmin). The model parameters were estimated in a Bayesian framework to produce probabilistic predictions of exceeding an island-specific outbreak threshold. The ability of the model to successfully detect outbreaks was assessed and compared to a baseline model, representative of standard dengue surveillance practice. Drought conditions were found to positively influence dengue relative risk at long lead times of up to 5 months, while excess rainfall increased the risk at shorter lead times between 1 and 2 months. The SPI averaged over a 6-month period (SPI-6), designed to monitor drought and extreme rainfall, better explained variations in dengue risk than monthly precipitation data measured in millimetres. Tmin was found to be a better predictor than mean and maximum temperature. Furthermore, including bidimensional exposure-lag-response functions of these indicators-rather than linear effects for individual lags-more appropriately described the climate-disease associations than traditional modelling approaches. In prediction mode, the model was successfully able to distinguish outbreaks from nonoutbreaks for most years, with an overall proportion of correct predictions (hits and correct rejections) of 86% (81%:91%) compared with 64% (58%:71%) for the baseline model. The ability of the model to predict dengue outbreaks in recent years was complicated by the lack of data on the emergence of new arboviruses, including chikungunya and Zika. CONCLUSION: We present a modelling approach to infer the risk of dengue outbreaks given the cumulative effect of climate variations in the months leading up to an outbreak. By combining the dengue prediction model with climate indicators, which are routinely monitored and forecasted by the Regional Climate Centre (RCC) at the Caribbean Institute for Meteorology and Hydrology (CIMH), probabilistic dengue outlooks could be included in the Caribbean Health-Climatic Bulletin, issued on a quarterly basis to provide climate-smart decision-making guidance for Caribbean health practitioners. This flexible modelling approach could be extended to model the risk of dengue and other arboviruses in the Caribbean region.