Browsing by Author "Diggle, P.J."

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Addressing the global snakebite crisis with geo-spatial analyses - Recent advances and future direction
(Elsevier Ltd, 2021) Pintor, A.F.V.; Ray, N.; Longbottom, J.; Bravo-Vega, C.A.; Yousefi, M.; Murray, K.A.; Ediriweera, D.S.; Diggle, P.J.
ABSTRACT: Venomous snakebite is a neglected tropical disease that annually leads to hundreds of thousands of deaths or long-term physical and mental ailments across the developing world. Insufficient data on spatial variation in snakebite risk, incidence, human vulnerability, and accessibility of medical treatment contribute substantially to ineffective on-ground management. There is an urgent need to collect data, fill knowledge gaps and address on-ground management problems. The use of novel, and transdisciplinary approaches that take advantage of recent advances in spatio-temporal models, 'big data', high performance computing, and fine-scale spatial information can add value to snakebite management by strategically improving our understanding and mitigation capacity of snakebite. We review the background and recent advances on the topic of snakebite related geospatial analyses and suggest avenues for priority research that will have practical on-ground applications for snakebite management and mitigation. These include streamlined, targeted data collection on snake distributions, snakebites, envenomings, venom composition, health infrastructure, and antivenom accessibility along with fine-scale models of spatio-temporal variation in snakebite risk and incidence, intraspecific venom variation, and environmental change modifying human exposure. These measures could improve and 'future-proof' antivenom production methods, antivenom distribution and stockpiling systems, and human-wildlife conflict management practices, while simultaneously feeding into research on venom evolution, snake taxonomy, ecology, biogeography, and conservation. KEYWORDS: Envenomings; Medically relevant snakes; Neglected tropical diseases; Snakebite incidence; Spatio-temporal epidemiology; Species distribution models.
Adjusting for spatial variation when assessing individual-level risk: A case-study in the epidemiology of snake-bite in Sri Lanka
(Public Library of Science, 2019) Ediriweera, D.S.; Kasturiratne, A.; Pathmeswaran, A.; Gunawardena, N.K.; Jayamanne, S.F.; Murray, K.; Iwamura, T.; Lalloo, D.G.; de Silva, H.J.; Diggle, P.J.
BACKGROUND:Health outcomes and causality are usually assessed with individual level sociodemographic variables. Studies that consider only individual-level variables can suffer from residual confounding. This can result in individual variables that are unrelated to risk behaving as proxies for uncaptured information. There is a scarcity of literature on risk factors for snakebite. In this study, we evaluate the individual-level risk factors of snakebite in Sri Lanka and highlight the impact of spatial confounding on determining the individual-level risk effects.METHODS:Data was obtained from the National Snakebite Survey of Sri Lanka. This was an Island-wide community-based survey. The survey sampled 165,665 individuals from all 25 districts of the country. We used generalized linear models to identify individual-level factors that contribute to an individual's risk of experiencing a snakebite event. We fitted separate models to assess risk factors with and without considering spatial variation in snakebite incidence in the country.RESULTS:Both spatially adjusted and non-adjusted models revealed that middle-aged people, males, field workers and individuals with low level of education have high risk of snakebites. The model without spatial adjustment showed an interaction between ethnicity and income levels. When the model included a spatial adjustment for the overall snakebite incidence, this interaction disappeared and income level appeared as an independent risk factor. Both models showed similar effect sizes for gender and age. HEmployment and education showed lower effect sizes in the spatially adjusted model.CONCLUSIONS:Both individual-level characteristics and local snakebite incidence are important to determine snakebite risk at a given location. Individual level variables could act as proxies for underling residual spatial variation when environmental information is not considered. This can lead to misinterpretation of risk factors and biased estimates of effect sizes. Both individual-level and environmental variables are important in assessing causality in epidemiological studies.
Development of a Snakebite risk map for Sri Lanka
(Sri Lanka Medical Association, 2016) Ediriweera, D.S.; Kasturiratne, A.; Pathmeswaran, A.; Gunawardena, N.K.; Wijayawickrama, B.A.; Jayamanne, S.F.; Isbister, G.K.; Dawson, A.; Giorgi, E.; Diggle, P.J.; Lalloo, D.G.; de Silva, H.J.
INTRODUCTION: Snakebite is a public health problem in Sri Lanka and about 37,000 patients are treated in government hospitals annually. At present, health care resources which are required to manage snakebite are distributed based on the administrative boundaries, rather than based on scientific risk assessment. OBJECTIVES: The aim of the study is to develop a snakebite risk map for Sri Lanka. METHOD: Epidemiological data was obtained from a community-based island-wide survey. The sample was distributed equally among the nine provinces. 165,665 participants (0.8%of the country’s population) living in 1118 Grama Niladhari divisions were surveyed. Generalized linear and generalized additive models were used for exploratory data analysis. Model-based geostatistics was used to determine the geographical distribution of snakebites. Monte Carlo maximum likelihood method was used to obtain parameter estimates and plug-in spatial predictions were obtained. Probability contour maps (PCM) were developed to demonstrate the spatial variation in the probability that local incidence does or does not exceed national snakebite incidence. RESULTS: Individual point estimate snakebite incidence map and PCM were developed to demonstrate the national incidence of snakebite in Sri Lanka. Snakebite hotspots and cold spots were identified in relation to the national snakebite incidence rate. Risk maps showed a within-country spatial variation in snakebites. CONCLUSIONS: The developed risk maps provide useful information for healthcare decision makers to allocate resources to manage snakebite in Sri Lanka.
Evaluating spatiotemporal dynamics of snakebite in Sri Lanka: Monthly incidence mapping from a national representative survey sample
(Public Library of Science, 2021) Ediriweera, D.S.; Kasturiratne, A.; Pathmeswaran, A.; Gunawardena, N.K.; Jayamanne, S.F.; Murray, K.; Iwamura, T.; Isbister, G.; Dawson, A.; Lalloo, D.G.; de Silva, H.J.; Diggle, P.J.
BACKGROUND: Snakebite incidence shows both spatial and temporal variation. However, no study has evaluated spatiotemporal patterns of snakebites across a country or region in detail. We used a nationally representative population sample to evaluate spatiotemporal patterns of snakebite in Sri Lanka. METHODOLOGY: We conducted a community-based cross-sectional survey representing all nine provinces of Sri Lanka. We interviewed 165 665 people (0.8% of the national population), and snakebite events reported by the respondents were recorded. Sri Lanka is an agricultural country; its central, southern and western parts receive rain mainly from Southwest monsoon (May to September) and northern and eastern parts receive rain mainly from Northeast monsoon (November to February). We developed spatiotemporal models using multivariate Poisson process modelling to explain monthly snakebite and envenoming incidences in the country. These models were developed at the provincial level to explain local spatiotemporal patterns. PRINCIPAL FINDINGS: Snakebites and envenomings showed clear spatiotemporal patterns. Snakebite hotspots were found in North-Central, North-West, South-West and Eastern Sri Lanka. They exhibited biannual seasonal patterns except in South-Western inlands, which showed triannual seasonality. Envenoming hotspots were confined to North-Central, East and South-West parts of the country. Hotspots in North-Central regions showed triannual seasonal patterns and South-West regions had annual patterns. Hotspots remained persistent throughout the year in Eastern regions. The overall monthly snakebite and envenoming incidences in Sri Lanka were 39 (95%CI: 38-40) and 19 (95%CI: 13-30) per 100 000, respectively, translating into 110 000 (95%CI: 107 500-112 500) snakebites and 45 000 (95%CI: 32 000-73 000) envenomings in a calendar year. CONCLUSIONS/SIGNIFICANCE: This study provides information on community-based monthly incidence of snakebites and envenomings over the whole country. Thus, it provides useful insights into healthcare decision-making, such as, prioritizing locations to establish specialized centres for snakebite management and allocating resources based on risk assessments which take into account both location and season.
Evaluating temporal patterns of snakebite in Sri Lanka: The potential for higher snakebite burdens with climate change
(Sri Lanka Medical Association, 2018) Ediriweera, D.S.; Diggle, P.J.; Kasturiratne, A.; Pathmeswaran, A.; Gunawardena, N.K.; Jayamanne, S.F.; Isbister, J.K.; Dawson, A.; Lalloo, D.G.; de Silva, H.J.
INTRODUCTION AND OBJECTIVES: Snakebite is a neglected tropical disease that has been overlooked by healthcare decision makers in many countries. Previous studies have reported seasonal variation in hospital admission rates due to snakebites in endemic countries including Sri Lanka, but seasonal patterns have not been investigated in detail. METHODS: A national community-based survey was conducted during the period of August 2012 to June 2013. The survey used a multistage cluster design, sampled 165,665 individuals living in 44,136 households and recorded all recalled snakebite events that had occurred during the preceding year Log-linear models were fitted to describe the expected number of snakebites occurring in each month taking into account seasonal trends and weather conditions, and addressing the effects of variation in survey effort during the study and due to recall bias amongst survey respondents RESULTS: Snakebite events showed a clear seasonal variation. Typically, snakebite incidence was highest during November to December followed by March to May and August, but this varied between years due to variations in relative humidity, which is also a risk-factor. Low relative humidity levels was associated with high snakebite incidence. If current climate change projections are correct, this could lead to an increase in the annual snakebite of burden of 35,086 (95% CI: 4 202 a€" 69,232) during the next 25 to 50 years. CONCLUSION: Snakebite in Sri Lanka shows seasonal variation Additionally, more snakebites can be expected during periods of lower than expected humidity. Global climate change is likely to increase the incidence of snakebite in Sri Lanka.
Evaluating temporal patterns of snakebite in Sri Lanka: the potential for higher snakebite burdens with climate change
(Oxford University Press, 2018) Ediriweera, D.S.; Diggle, P.J.; Kasturiratne, A.; Pathmeswaran, A.; Gunawardena, N.K.; Jayamanne, S.K.; Isbister, G.K.; Dawson, A.; Lalloo, D.G.; de Silva, H.J.
BACKGROUND: Snakebite is a neglected tropical disease that has been overlooked by healthcare decision makers in many countries. Previous studies have reported seasonal variation in hospital admission rates due to snakebites in endemic countries including Sri Lanka, but seasonal patterns have not been investigated in detail. METHODS: A national community-based survey was conducted during the period of August 2012 to June 2013. The survey used a multistage cluster design, sampled 165 665 individuals living in 44 136 households and recorded all recalled snakebite events that had occurred during the preceding year. Log-linear models were fitted to describe the expected number of snakebites occurring in each month, taking into account seasonal trends and weather conditions, and addressing the effects of variation in survey effort during the study and of recall bias amongst survey respondents. ResulTS: Snakebite events showed a clear seasonal variation. Typically, snakebite incidence is highest during November–December followed by March–May and August, but this can vary between years due to variations in relative humidity, which is also a risk factor. Low relative-humidity levels are associated with high snakebite incidence. If current climate-change projections are correct, 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. CONCLUSIONS: Snakebite in Sri Lanka shows seasonal variation. Additionally, more snakebites can be expected during periods of lower-than-expected humidity. Global climate change is likely to increase the incidence of snakebite in Sri Lanka.
Individual risk factors of snakebites in Sri Lankan community
(Faculty of Graduate Studies, University of Kelaniya, 2015) Ediriweera, E.P.D.S.; Pathmeswaran, A.; Kasturiratne, A.; Gunawardana, N.K.; Jayamanne, S.F.; de Silva, H.J.; Diggle, P.J.
Sri Lanka has 92 identified snake species, and one of the highest snakebite incidence (SBI) rates in the world. According to hospital statistics about 37,000 patients are admitted to government hospitals annually as a result of snakebite. The aim of the present study is to identify individual risk factors for snakebite in Sri Lanka. Methodology A community-based island-wide study (―National Snakebite Study‖) was conducted in all nine provinces of Sri Lanka, with 5,000 households sampled in each province. All the residents of the selected households were included. One-year recall data for all permanent residents of that particular household was obtained regarding the experience of snakebite. Generalized linear models were used to model SBI. Individual-level gender, age, ethnicity, religion, income, education and employment were included as explanatory variables. Statistical analysis used the R programming language. Statistical significance was assessed at the 0.01 level. Results and conclusions Out of 125,391 participants, 63,604 (50.7%) were males. There was no SBI difference amongst 10-year interval age groups from 30 to 59, hence these three age groups were collapsed. High SBI was observed in the age 30-59 year group compared to age less than 20 (P<0.001), 20 to 29 (P<0.001), 60 to 69 (P<0.003) and over 70 (P<0.007), with lower SBI in the two extreme age groups. Males had higher SBI compared to females (P<0.001). Field workers had higher SBI compared to non-field workers (P<0.001). Ethnicity and income showed a significant interaction. Low income non-Sinhalese had high SBI compared to middle income (Rs. 5000-19,999, P<0.001) and high income (Rs.>20,000, P=0.001) non- Sinhalese, whereas Sinhalese had high SBI irrespective of their income status. In summary, the high risk categories for snakebites are males, field workers, 30 – 60 year individuals, Sinhalese and low income non-Sinhalese.
Integrating snake distribution, abundance and expert-derived behavioural traits predicts snakebite risk
(Wiley-Blackwell, 2022) Martín, G.; Erinjery, J.; Gumbs, R.; Somaweera, R.; Ediriweera, D.; Diggle, P.J.; Kasturiratne, A.; de Silva, H.J.; Lalloo, D.G.; Iwamura, T.; Murray, K. A.
Despite important implications for human health, distribution, abundance and behaviour of most medically-relevant snakes remain poorly understood. Such data deficiencies hamper efforts to characterise the causal pathways of snakebite envenoming and to prioritise management options in the areas at greatest risk. We estimated the spatial patterns of abundance of seven medically-relevant snake species from Sri Lanka, a snakebite hotspot, and combined them with indices of species’ relative abundance, aggressiveness and envenoming severity obtained from an expert opinion survey to test whether these fundamental ecological traits could explain spatial patterns of snakebite and envenoming incidence. The spatial intensity of snake occurrence records in relation to independent environmental factors (fundamental niches and land cover) was analysed with point process models. Then, with the estimated patterns of abundance, we tested which species’ abundances added together, with and without weightings for aggressiveness, envenoming severity and relative abundance, best correlate with per-capita geographic incidence patterns of snakebite and envenoming. We found that weighting abundance patterns by species’ traits increased correlation with incidence. The best performing combination had three species weighted by aggressiveness and abundance, with a correlation of r = 0.47 (P < 0.01) with snakebite incidence. An envenoming severity and relative abundance-weighted combination of two species was the most strongly associated with envenoming incidence (r = 0.46, P = 0). SYNTHESIS AND APPLICATIONS. We show that snakebite risk is explained by abundance, aggressiveness and envenoming severity of the snake species most frequently involved in envenoming cases. Incorporating causality via ecological information of key snake species is critical for snakebite risk mapping, help to tailor preventive measures for dominant snake species and deploy the necessary antivenom therapies.
Mapping the risk of snakebite in Sri Lanka - A national survey with geospatial analysis
(Public Library of Science, 2016) Ediriweera, E.P.D.S.; Kasturiratne, A.; Pathmeswaran, A.; Gunawardena, N.K.; Wijayawickrama, B.A.; Jayamanne, S.F.; Isbister, G.K.; Dawson, A.; Giorgi, E.; Diggle, P.J.; Lalloo, D.G.; de Silva, H.J.
BACKGROUND: There is a paucity of robust epidemiological data on snakebite, and data available from hospitals and localized or time-limited surveys have major limitations. No study has investigated the incidence of snakebite across a whole country. We undertook a community-based national survey and model based geostatistics to determine incidence, envenoming, mortality and geographical pattern of snakebite in Sri Lanka. METHODOLOGY/PRINCIPAL FINDINGS: The survey was designed to sample a population distributed equally among the nine provinces of the country. The number of data collection clusters was divided among districts in proportion to their population. Within districts clusters were randomly selected. Population based incidence of snakebite and significant envenoming were estimated. Model-based geostatistics was used to develop snakebite risk maps for Sri Lanka. 1118 of the total of 14022 GN divisions with a population of 165665 (0.8%of the country’s population) were surveyed. The crude overall community incidence of snakebite, envenoming and mortality were 398 (95% CI: 356–441), 151 (130–173) and 2.3 (0.2–4.4) per 100000 population, respectively. Risk maps showed wide variation in incidence within the country, and snakebite hotspots and cold spots were determined by considering the probability of exceeding the national incidence. CONCLUSIONS/SIGNIFICANCE: This study provides community based incidence rates of snakebite and envenoming for Sri Lanka. The within-country spatial variation of bites can inform healthcare decision making and highlights the limitations associated with estimates of incidence from hospital data or localized surveys. Our methods are replicable, and these models can be adapted to other geographic regions after re-estimating spatial covariance parameters for the particular region.