Health in a changing climate: the dynamic challenge of snake bite in South Asia

Lead Research Organisation: Liverpool School of Tropical Medicine
Department Name: Clinical Sciences

Abstract

Snakebite is a neglected tropical disease (NTD) and despite being less well publicised and studied, has a far greater impact than many other NTDs such as dengue or leishmaniasis. There are estimates of up to 120,000 deaths per year globally with considerable additional morbidity resulting, for example, from limb damage or renal failure. This burden of disease is relatively hidden as snakebite not only predominantly affects poorer countries in the tropics and subtropics, but it also mainly affects the rural poor, particularly agricultural workers and subsistence farmers in lower-middle income countries (LMICs).

In many countries, snakebite is seasonal and is distributed unevenly across a country because of complex interactions between human behaviour, climate, varying geography and other factors affecting snake distributions. This means that there are substantial challenges in estimating the number of deaths and complications of snakebite. National surveys are rare because they are so difficult to carry out. The variation in numbers of snakebite across countries and over any one year means that it is difficult to estimate national and regional numbers from time-limited small local studies. This absence of accurate numbers for many countries and regions means that the problem does not get the international attention that it requires and makes it extremely difficult for local public health authorities to plan appropriate health services.

Improved methodological approaches for mapping snakebite risk are therefore urgently needed, particularly when considering the potential for global environmental and climate change to exacerbate snakebite impacts. Examples such as the peak of snakebite deaths in India during the monsoon and in Bangladesh during floods illustrate the potential for environmental factors to influence disease. In Sri Lanka, bite and envenoming patterns also vary between climatic zones, with bite and envenoming incidence changing with altitude and rainfall. Climate change is thus likely to be an important yet currently unrecognised contributor to altering snakebite risk in affected areas, potentially impacting on snakebite incidence by altering snake abdundance, distributions and behaviour, altering human abundance and behaviour or both.

This study aims to improve the ways in which the epidemiological burden of snakebite can be estimated and mapping risk using modelling of the interactions between snake and human distributions, behaviours and environmental factors and to investigate the extent to which climate and land-use change will impact upon this burden. The study will develop and validate methodologies using data from Sri Lanka and, in future, use these approaches to improve estimations of the snakebite burden and map risk over wider geographical areas in South Asia, and predict how they may change in the future. This approach will facilitate the diversion of appropriate resources towards addressing this major problem and will provide accurate information about the distribution of the snakebite burden at relevant scales to help health managers target resources appropriately and explore interventions that will help manage this risk and its associated socio-economic impacts in LMICs.

Technical Summary

Snakebite is a neglected tropical disease (NTD) and despite being less well studied, has a far greater impact than many other NTDs. There are estimates of up to 120,000 deaths per year globally with major morbidity also resulting from limb damage or renal failure. This burden predominantly affects the rural poor, particularly agricultural workers and subsistence farmers in lower-middle income countries (LMICs) in the tropics/subtropics. There is considerable seasonal and geospatial variation of snakebite because of complex interactions between human behaviour, climate, geography and other factors affecting snake distributions. Burden estimates are difficult: health system statistics are flawed, national surveys are logistically difficult to do and complex variation makes it difficult to estimate national burdens from small local studies. Variation also means that changing environmental, ecological and human conditions could influence this burden.

This new collaboration brings together experts in snakebite, epidemiology, ecology and environmental change science to develop spatially explicit predictions for snakebite risk in a changing climate or land-use environment. We will first update our 2008 global burden of disease study and risk factor analysis to provide the global and regional context for subsequent national-scale research. Then, using Sri Lanka as a study system, we aim to better understand the spatial and temporal variation in snake bite by focusing on the human-snake contact rate. To do this, we will a) develop high resolution distribution models for important venomous snake species and identify how their distributions are shaped by environmental variables, b) generate a snake bite exposure index and validate it with existing detailed epidemiological data on snake bite, envenoming and mortality patterns and c) undertake activity profiling to assess the impact of climate change and land-use on snake and human behaviours and upon these models.

Planned Impact

Snakebite is predominantly a problem of the rural poor in the poorest LMICs (1). The greatest burden occurs in South and South-East Asia, sub-Saharan Africa (particularly West Africa) and parts of the South American continent. This application is focused on Sri-Lanka and South Asia, but the methodologies that will be developed will be applicable to all regions where there is a substantial snakebite problem. Snakebite has both significant health consequences (morbidity and mortality) and socio-economic consequences for health systems and households. This application is therefore clearly is line with the principles of ODA.

The project will make important contributions to the study and understanding of the epidemiology of snake bite and establish a novel agenda for understanding and potentially addressing the consequences of global change. Specific outcomes/deliverables will include:

a) Development of a collaborative network across South Asia to facilitate research and follow-on studies and produce an expert opinion report
b) Publication of a 10 year update to the global burden of snake bite study using new methodology
c) Robust global predictive models describing spatial variation in the snake bite burden
d) A venomous snake spatio-temporal occurrence database for South Asia (VenBank)
e) Venomous snake spatio-temporal models for Sri Lanka
f) Socio-ecological snake bite risk models for Sri Lanka
g) Projections (simulations) of future snake bite burden under scenarios of global climate and land-use change.

These outputs will have impact in a number of ways.

The development of regional partnerships, collation of available data and validation of our approach will allow us to begin to apply our methods from Sri Lanka to other countries where data are currently more limited. Our methods will be transferrable, open-source, replicable and adaptable to other geographic regions. Improved spatially-explicit models offer numerous opportunities to improve management and data collection for future risk assessment and reduction activities, including enhancing surveillance (e.g., by establishing sentinel surveillance nodes in high risk areas), optimising interventions (e.g., directing protective equipment and anti-venom supplies to areas of high risk), informing healthcare decision making (e.g., identifying locations for establishing snake bite management centres), or for systematically obtaining additional samples from under-sampled locations to reduce uncertainty and improve representativeness of burden estimates. Better understanding of the main drivers behind human snakebite risk may ultimately allow discussion and design of focused preventative interventions.

Internationally, updated burden estimates and change scenarios will help to support international efforts to raise the profile of snakebite as a neglected tropical disease. These efforts have recently commenced, sparked by a global crisis in antivenom supply, and culminating in discussion of the issue at the World Health Assembly (May 2016). Deficiencies in burden estimation and snakebite epidemiology were recently identified as a barrier to progress at an international consensus meeting at Hinxton in 2015 and this study will help to address this. Better scientific understanding of the health impacts of climate change also help to garner global support for meeting the COP21 targets and other parallel post-2015 health, environmental, and sustainable development targets and for implementing WHO's Generic framework for control, elimination and eradication of neglected tropical diseases.

1) Harrison RA, Hargreaves A, Wagstaff SC, Faragher B, Lalloo DG. Snake envenoming: a disease of poverty. PLoS Negl Trop Dis. 2009 Dec 22;3(12):e569. doi: 10.1371/journal.pntd.0000569

Publications

10 25 50
 
Description New ways of potentially predicting snakebite risk
Exploitation Route Better snakebite risk models
Sectors Communities and Social Services/Policy,Healthcare

 
Description Antivenom clinical trial development
Amount £112,276 (GBP)
Funding ID 217264/Z/19/Z 
Organisation Wellcome Trust 
Sector Charity/Non Profit
Country United Kingdom
Start 04/2019 
End 10/2020
 
Description NTD Modelling Consortium: moving towards elimination
Amount $447,364 (USD)
Funding ID OPP1184344 
Organisation Bill and Melinda Gates Foundation 
Sector Charity/Non Profit
Country United States
Start 01/2017 
End 01/2021
 
Title Agent-based model to estimate snakebite risk based on snake-farmer interation 
Description Allows prediction of temporal and seasonal risks of snakebite related to snake and farmer activity 
Type Of Material Model of mechanisms or symptoms - human 
Year Produced 2020 
Provided To Others? No  
Impact Too early 
 
Title Future land use prediction model based on CLUE-s model 
Description Model to predict changing land use 
Type Of Material Model of mechanisms or symptoms - human 
Year Produced 2019 
Provided To Others? No  
Impact Premature 
 
Title Methods to analyse the ecological niche of snake species 
Description methods to analyse the ecological niche of snake species in Sri Lanka and their corresponding distributions based on records of their occurrence 
Type Of Material Model of mechanisms or symptoms - mammalian in vivo 
Year Produced 2017 
Provided To Others? No  
Impact no 
 
Title Multivariate models to estimate local spatiotemporal variations in bite incidence 
Description We used data from the Sri Lanka national snakebite survey (165,665 people) living in 1,118 clusters representing all the provinces of the country) to develop and fit a novel class of multivariate Poisson process models to local spatiotemporal variations in bite incidence (paper in preparation). 
Type Of Material Model of mechanisms or symptoms - human 
Year Produced 2019 
Provided To Others? No  
Impact Paper in process 
 
Title Snakebite epi research methods and tools 
Description Snakebite epi research methods and tools developed and implemented in R (spatstat, raster, rgdal, spdep), QGIS, JAGS, NicheA, Imperial High Powered Computing (HPC 
Type Of Material Model of mechanisms or symptoms - human 
Year Produced 2019 
Provided To Others? No  
Impact Premature 
 
Title protocol to categorize land cover types in Sri Lanka 
Description protocol to categorize land cover types in Sri Lanka based on satellite imagery. This method can distinguish dense forests, degraded forests, agricultural lands, and urban areas at 30 metre resolution for multiple time periods. 
Type Of Material Model of mechanisms or symptoms - human 
Year Produced 2017 
Provided To Others? No  
Impact no 
 
Title Agent based simulation 
Description Following on from development of a simple trial model for the agent-based simulation component of the project, an agent based model has been developed that is capable of representing both human behavior and snake behavior across landscapes that were classified using remote sensing. The outcome of this model is locations and time periods where snakebites occur, and through this model we are capable of exploring the way in which land use and land cover change may affect snakebites. 
Type Of Material Computer model/algorithm 
Year Produced 2018 
Provided To Others? No  
Impact None yet 
 
Title Environmental and socioeconomic datasets 
Description Environmental and socioeconomic datasets (obtained or derived from public repositories (e.g., WorldClim, SRTM, GPWv4, CIESIN, CRU), or developed by team members (J. Erinjery)). 
Type Of Material Database/Collection of data 
Year Produced 2018 
Provided To Others? No  
Impact None yet 
 
Title Future land cover dataset for Sri Lanka based on CLUE-s model 
Description Estimated future trends for change in land use 
Type Of Material Database/Collection of data 
Year Produced 2019 
Provided To Others? No  
Impact Premature 
 
Title Global Incidence of snakebite 
Description A comprehensive review of published, grey literature and burden databases has been undertaken to identify all global epidemiological data on snakebite incidence. Initial analysis has been undertaken to estimate global burden 
Type Of Material Database/Collection of data 
Year Produced 2019 
Provided To Others? No  
Impact None yet 
 
Title Historical land cover dataset based on remote sensing land classification for Sri Lanka 
Description Detailed land use maps at 30 m resolution have been created for Sri Lanka, which was used as input for snake bite risk modelling, agent based modelling, and land-use change modelling. The maps were developed using remotely sensed images (Landsat data) and were made for years 2004, 2007, 2010, 2013 and 2017 (Figure 1). 
Type Of Material Database/Collection of data 
Year Produced 2018 
Provided To Others? No  
Impact None yet 
 
Title Satellite datasets Sri Lanka 
Description Cleaned satellite image dataset for Sri Lanka 
Type Of Material Database/Collection of data 
Year Produced 2018 
Provided To Others? No  
Impact no 
 
Title Seasonal variation snakebite model 
Description Study of temporal patterns of snakebite in Sri Lanka found there is clear seasonal variation in snakebite in Sri Lanka. Typically, the highest incidence is noticed during November - December followed by March-May and August. Low humidity levels also appeared as a risk factor indicating increase snakebite incidence can be expected during dry months. According to the representative concentration pathways' (RCP) intermediate scenarios (i.e. RCP 4.5 and RCP 6), Sri Lanka will experience an increase of approximately 0.5 - 1.0 during the next 25 to 50 years and this could lead to an increase in the annual snakebite burden of 31.3% (95% confidence interval: 10.7-55.7) during the next 25-50 years 
Type Of Material Computer model/algorithm 
Year Produced 2018 
Provided To Others? Yes  
Impact too early 
 
Title Snake species abundance model 
Description Modelling of the distribution of the venomous snake species in Sri Lanka as Poisson point processes to reflect an index of abundance Generation of four maps of snake abundance, one by strict addition, then weighted by species aggressiveness, envenoming severity and aggressiveness x severity. Subsequent work has found statistical evidence that snakebites are the product of both human and snake abundance. Snake abundance however is affected by human populations, which results in a negative effect of humans on snakebite risk. Based on this inference, a mechanistic model has been generated that represents the competition between humans and snakes, and how snakebites occur as the result of the overlap between snakes and people. The identified mechanisms suggest that as human populations grow, snake populations could decline, and so would do snakebite incidence. The number of people bitten per year, however, would keep increasing mainly driven by population growth. 
Type Of Material Computer model/algorithm 
Year Produced 2018 
Provided To Others? No  
Impact too early 
 
Title Spatial snake and human population model 
Description Model collates the spatial data on snake distributions and human populations to enable us to estimate snake-human contact rates. With these analyses we intend to generate a mechanistic model that is able to reproduce the observed temporal patterns of snakebite incidence in some populations in Sri Lanka. 
Type Of Material Data analysis technique 
Year Produced 2018 
Provided To Others? No  
Impact None yet 
 
Title Spatio-temporal incidence modelling 
Description Combination of spatial and temporal risk factors to develop a spatiotemporal model to understand the spatiotemporal dynamics of snakebite in Sri Lanka. Seasonal snakebite risk maps have been produced to identify persistent and transient snakebite hot-spots in Sri Lanka. This will help policymakers to identify snakebite risk at a given location in a given time. 
Type Of Material Data analysis technique 
Year Produced 2018 
Provided To Others? Yes  
Impact Too early 
 
Title Venbank 
Description Online database and data portal (venbank.info) which contains multiple databases relevant to snakebite prediction for public interrogation and exploration). Plans to develop into citizen science data collection app, risk communication tool, information repository for stakeholders (funding sought). 
Type Of Material Database/Collection of data 
Year Produced 2018 
Provided To Others? Yes  
Impact None 
 
Description Generation of Snake Models 
Organisation National Autonomous University of Mexico
Country Mexico 
Sector Academic/University 
PI Contribution Research stay by PDRA in laboratory to facilitate generation of snake models to Venbank.
Collaborator Contribution Generation of data for Venbank
Impact None yet
Start Year 2019
 
Description Tel Aviv University (TAU)- Imperial- Kelaniya- CSIRo 
Organisation Commonwealth Scientific and Industrial Research Organisation
Country Australia 
Sector Public 
PI Contribution Planned study and identified herpetologists in Sri Lanka and Australia
Collaborator Contribution Helped to explore existing sources of data and lead herpetological activities
Impact Venomous snake occurrence data
Start Year 2017
 
Title R code for modelling of snakebite occurrence 
Description Snake models: R scripts for model selection and data formatting Snakebite models: R and JAGS scripts for model selection Scripts for model visualisation Scripts for model simulations Climate downscales Scripts for downscaling CORDEXSA Scripts for validating downscales Herpetologists questionnaire and statistical analyssis of the questionnaire Venbank - online database and data portal (venbank.info) 
Type Of Technology Software 
Year Produced 2019 
Impact None yet