Spatial epidemiology of suspected clinical leptospirosis in Sri Lanka

Defining Spatial Epidemiology: A Systematic Review and Re-orientation

BACKGROUND

Spatial epidemiology has emerged as an important subfield of epidemiology over the past quarter century. We trace the origins of spatial epidemiology and note that its emergence coincided with technological developments in spatial statistics and geography. We hypothesize that spatial epidemiology makes important contributions to descriptive epidemiology and analytic risk-factor studies but is not yet aligned with epidemiology's current focus on causal inference and intervention.

METHODS

We conducted a systematic review of studies indexed in PubMed that used the term "spatial epidemiolog*" in the title, abstract, or keywords. Excluded articles were not written in English, examined disease in animals, or reported biologic pathogen distribution only. We coded the included papers into five categories (review, demonstration of method, descriptive, analytic, and intervention) and recorded the unit of analysis (i.e., individual vs. ecological). We additionally examined articles coded as analytic ecologic studies using scales for lexical content.

RESULTS

A total of 482 articles met the inclusion criteria, including 76 reviews, 117 demonstrations of methods, 122 descriptive studies, 167 analytic studies, and 0 intervention studies. Demonstration studies were most common from 2006 to 2014, and analytic studies were most common after 2015. Among the analytic ecologic studies, those published in later years used more terms relevant to spatial statistics (incidence rate ratio =1.3; 95% confidence interval [CI] = 1.1, 1.5) and causal inference (incidence rate ratio =1.1; 95% CI = 1.1, 1.2).

CONCLUSIONS

Spatial epidemiology is an important and growing subfield of epidemiology. We suggest a re-orientation to help align its practice with the goals of contemporary epidemiology.

SARIMA and ARDL models for predicting leptospirosis in Anuradhapura district Sri Lanka

Leptospirosis is considered a neglected tropical disease despite its considerable mortality and morbidity. Lack of prediction remains a major reason for underestimating the disease. Although many models have been developed, most of them focused on the districts situated in the wet zone due to higher case numbers in that region. However, leptospirosis remains a major disease even in the dry zone of Sri Lanka. The objective of this study is to develop a time series model to predict leptospirosis in the Anuradhapura district situated in the dry zone of Sri Lanka. Time series data on monthly leptospirosis incidences from January 2008 to December 2018 and monthly rainfall, rainy days, temperature, and relative humidity were considered in model fitting. The first 72 months (55%) were used to fit the model, and the subsequent 60 months(45%) were used to validate the model. The log-transformed dependent variable was employed for fitting the Univariate seasonal ARIMA model. Based on the stationarity of the mean of the five variables, the ARDL model was selected as the multivariate time series technique. Residuals analysis was performed on normality, heteroskedasticity, and serial correlation to validate the model. The lowest AIC and MAPE were used to select the best model. Univariate models could not be fitted without adjusting the outliers. Adjusting seasonal outliers yielded better results than the models without adjustments. Best fitted Univariate model was ARIMA(1,0,0)(0,1,1)₁₂,(AIC-1.08, MAPE-19.8). Best fitted ARDL model was ARDL(1, 3, 2, 1, 0),(AIC-2.04,MAPE-30.4). The number of patients reported in the previous month, rainfall, rainy days, and temperature showed a positive association, while relative humidity was negatively associated with leptospirosis. Multivariate models fitted better than univariate models for the original data. Best-fitted models indicate the necessity of including other explanatory variables such as patient, host, and epidemiological factors to yield better results.

Effects of rainfall on human leptospirosis in Thailand: evidence of multi-province study using distributed lag non-linear model

Leptospirosis is a zoonotic bacterial disease that remains an important public health problem, especially in tropical developing countries. Many previous studies in Thailand have revealed the outbreak of human leptospirosis after heavy rainfall, but research determining its quantitative risks associated with rainfall, especially at the national level, remains limited. This study aims to examine the association between rainfall and human leptospirosis across 60 provinces of Thailand. A quasi-Poisson regression framework combined with the distributed lag non-linear model was used to estimate province-specific association between rainfall and human leptospirosis, adjusting for potential confounders. Province-specific estimates were then pooled to derive regional and national estimates using random-effect meta-analysis. The highest risk of leptospirosis associated with rainfall at national level was observed at the same month (lag 0). Using 0 cm/month of rainfall as a reference, the relative risks of leptospirosis associated with heavy (90th percentile), very heavy (95th percentile), and extremely heavy (99th percentile) rainfall at the national level were 1.0994 (95% CI 0.9747, 1.2401), 1.1428 (95% CI 1.0154, 1.2862), and 1.1848 (95% CI 1.0494, 1.3378), respectively. The highest risk of human leptospirosis associated with rainfall was observed in the northern and north-eastern regions. Specifically, the relative risks of leptospirosis associated with extremely heavy rainfall in northern and north-eastern regions were 1.2362 (95% CI 0.9110, 1.6775) and 1.2046 (95% CI 0.9728, 1.4918), respectively. Increasing rainfall was associated with increased risks of leptospirosis, especially in the northern and northeastern regions of Thailand. This finding could be used for precautionary warnings against heavy rainfall.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00477-022-02250-x.

Unraveling the invisible leptospirosis in mainland Southeast Asia and its fate under climate change

Leptospirosis is a neglected waterborne zoonosis of growing concern in tropical and low-income regions. Endemic in Southeast Asia, its distribution and environmental factors such as climate controlling its dynamics remain poorly documented. In this paper, we investigate for the first time the current and future leptospirosis burden at a local scale in mainland Southeast Asia. We adjusted machine-learning models on incidence reports from the Thai surveillance system to identify environmental determinants of leptospirosis. The explanatory variables tested in our models included climate, topographic, land cover and soil variables. The model performing the best in cross-validation was used to estimate the current incidence regionally in Thailand, Myanmar, Cambodia, Vietnam and Laos. It then allowed to predict the spatial distribution of leptospirosis future burden from 2021 to 2100 based on an ensemble of CMIP6 climate model projections and 4 Shared Socio-economics Pathways ranging from the most optimistic to the no-climate policy outcomes (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5). Leptospirosis incidence was best estimated by 10 environmental variables: four landscape-, four rainfall-, two temperature-related variables. Of all tested scenario, the worst-case scenario of climate change (SSP5-8.5) surprisingly appeared as the best-case scenario for the future of leptospirosis since it would induce a significant global decline in disease incidence in Southeast Asia mainly driven by the increasing temperatures. These global patterns are however contrasted regionally with some regions showing increased incidence in the future. Our work highlights climate and the environment as major drivers of leptospirosis incidence in Southeast Asia. Applying our model to regions where leptospirosis is not routinely monitored suggests an overlooked burden in the region. As our model focuses on leptospirosis responses to environmental drivers only, some other factors, such as poverty, lifestyle or behavioral changes, could further influence these estimated future patterns.

Leptospira Is an Environmental Bacterium That Grows in Waterlogged Soil

Leptospirosis is a zoonotic disease caused by infection with pathogenic leptospires. Consistent with recent studies by other groups, leptospires were isolated from 89 out of 110 (80.9%) soil or water samples from varied locations in the Philippines in our surveillance study, indicating that leptospires might have a life cycle that does not involve animal hosts. However, despite previous work, it has not been confirmed whether leptospires multiply in the soil environment under various experimental conditions. Given the fact that the case number of leptospirosis is increased after flood, we hypothesized that waterlogged soil, which mimics the postflooding environment, could be a suitable condition for growing leptospires. To verify this hypothesis, pathogenic and saprophytic leptospires were seeded in the bottles containing 2.5 times as much water as soil, and bacterial counts in the bottles were measured over time. Pathogenic and saprophytic leptospires were found to increase their number in waterlogged soil but not in water or soil alone. In addition, leptospires were reisolated from soil in closed tubes for as long as 379 days. These results indicate that leptospires are in a resting state in the soil and are able to proliferate with increased water content in the environment. This notion is strongly supported by observations that the case number of leptospirosis is significantly higher in rainy seasons and increased after flood. Therefore, we reached the following conclusion: environmental soil is a potential reservoir of leptospires.

IMPORTANCE Since research on Leptospira has focused on pathogenic leptospires, which are supposed to multiply only in animal hosts, the life cycle of saprophytic leptospires has long been a mystery. This study demonstrates that both pathogenic and saprophytic leptospires multiply in the waterlogged soil, which mimics the postflooding environment. The present results potentially explain why leptospirosis frequently occurs after floods. Therefore, environmental soil is a potential reservoir of leptospires and leptospirosis is considered an environment-borne as well as a zoonotic disease. This is a significant report to reveal that leptospires multiply under environmental conditions, and this finding leads us to reconsider the ecology of leptospires.

Eco-epidemiological scaling of Leptospirosis: Vulnerability mapping and early warning forecasts

Infectious disease epidemics are plaguing the world and a lot of research is focused on the development of models to reproduce disease dynamics for eco-environmental and biological investigation, and disease management. Leptospirosis is an example of a neglected zoonosis strongly mediated by ecohydrological dynamics with emerging endemic and epidemic patterns worldwide in both animal and human populations. By accounting for large heterogeneities of affected areas we show how exponential endemics and scale-free epidemics are largely predictable and linked to common socio-environmental features via scaling laws with different exponents that inform about vulnerability factors. This led to the development of a novel pattern-oriented integrated model that can be used as an early-warning signal (EWS) tool for endemic-epidemic regime classification, risk determinant attribution, and near real-time forecast of outbreaks. Forecasts are grounded on expected outbreak recurrence time dependent on exceedance probabilities and statistical EWS that sense outbreak onset. A stochastic spatially-explicit model is shown to comprehensively predict outbreak dynamics (early sensing, timing, magnitude, decay, and eco-environmental determinants) and derive a spreading factor characterizing endemics and epidemics, where average over maximum rainfall is the critical factor characterizing disease transitions. Dynamically, case cross-correlation considering neighboring communities senses 2-weeks in advance outbreaks. Eco-environmental scaling relationships highlight how predicted host suitability and topographic index can be used as epidemiological footprints to effectively distinguish and control Leptospirosis regimes and areas dependent on hydro-climatological dynamics as the main trigger. The spatio-temporal scale-invariance of epidemics - underpinning persistent criticality and neutrality or independence among areas - is emphasized by the high accuracy in reproducing sequence and magnitude of cases via reliable surveillance. Further investigations of robustness and universality of eco-environmental determinants are required; nonetheless a comprehensive and computationally simple EWS method for the full characterization of Leptospirosis is provided. The tool is extendable to other climate-sensitive zoonoses to define vulnerability factors and predict outbreaks useful for optimal disease risk prevention and control.

Time series models for prediction of leptospirosis in different climate zones in Sri Lanka

In tropical countries such as Sri Lanka, where leptospirosis—a deadly disease with a high mortality rate—is endemic, prediction is required for public health planning and resource allocation. Routinely collected meteorological data may offer an effective means of making such predictions. This study included monthly leptospirosis and meteorological data from January 2007 to April 2019 from Sri Lanka. Factor analysis was first used with rainfall data to classify districts into meteorological zones. We used a seasonal autoregressive integrated moving average (SARIMA) model for univariate predictions and an autoregressive distributed lag (ARDL) model for multivariable analysis of leptospirosis with monthly average rainfall, temperature, relative humidity (RH), solar radiation (SR), and the number of rainy days/month (RD). Districts were classified into wet (WZ) and dry (DZ) zones, and highlands (HL) based on the factor analysis of rainfall data. The WZ had the highest leptospirosis incidence; there was no difference in the incidence between the DZ and HL. Leptospirosis was fluctuated positively with rainfall, RH and RD, whereas temperature and SR were fluctuated negatively. The best-fitted SARIMA models in the three zones were different from each other. Despite its known association, rainfall was positively significant in the WZ only at lag 5 (P = 0.03) but was negatively associated at lag 2 and 3 (P = 0.04). RD was positively associated for all three zones. Temperature was positively associated at lag 0 for the WZ and HL (P < 0.009) and was negatively associated at lag 1 for the WZ (P = 0.01). There was no association with RH in contrast to previous studies. Based on altitude and rainfall data, meteorological variables could effectively predict the incidence of leptospirosis with different models for different climatic zones. These predictive models could be effectively used in public health planning purposes.

Epidemiology of human leptospirosis in urban and rural areas of Brazil, 2000-2015

Background

Leptospirosis is one of the most widespread zoonosis in the world and Brazil has the highest number of cases in Latin America. Transmission occurs mainly through exposure to water and soil contaminated by the urine of infected animals. The goals of this study are to describe the geographic distribution, demographic characteristics and exposure factors of urban and rural cases of leptospirosis, and identify spatial clusters in urban and rural areas of Brazil.

Methods/results

A retrospective epidemiological study was carried out using 16 years (2000–2015) of surveillance data from the Brazilian Ministry of Health. Cases were described by age, sex and race, and exposure factors were characterized in urban and rural areas. A spatial autocorrelation analysis was conducted using local Moran’s I to identify urban and rural clusters of disease. On average 3,810 leptospirosis cases were reported annually with higher numbers in urban areas. National urban and rural incidence rates were the same (1.9 cases/100,000 population), however, regional differences were observed. Urban incidence rates were higher in the North and Northeast regions, while rural incidence rates were higher in the Southeast and South. The main exposure factor reported in urban and rural areas was exposure to places with signs of rodents, followed by flood in urban areas and agriculture and animal farming in rural areas. Clusters of leptospirosis were identified in densely populated urban areas of the North, Southeast and South regions, while rural clusters were concentrated in of the Southern region with large agriculture and animal farming practices.

Conclusions

This study highlights that leptospirosis is an important public health problem in both urban and rural areas of Brazil. The results provide decision-makers with detailed information about where disease incidence is high and can be used in the development of prevention and control strategies for priority areas and risk groups.

Effects of meteorological factors on human leptospirosis in Colombia

Leptospirosis is a disease usually acquired by humans through water contaminated with the urine of rodents that comes into direct contact with the cutaneous lesions, eyes, or mucous membranes. The disease has an important environmental component associated with climatic conditions and natural disasters, such as floods. We analyzed the relationship between rainfall and temperature and the incidence of leptospirosis in the top 30 municipalities with the highest numbers of cases of the disease in the period of 2007 to 2016. It was an ecological study of the time series of cases of leptospirosis, rainfall, and temperature with lags of 0, 1, 2, 3, and 4 weeks. A multilevel negative binomial regression model was implemented to evaluate the relationship between leptospirosis and both meteorological factors. In the 30 evaluated municipalities during the study period, a total of 5136 cases of leptospirosis were reported. According to the implemented statistical model, there was a positive association between the incidence of leptospirosis and rainfall with a lag of 1 week and a negative association with temperature with a lag of 4 weeks. Our results show the importance of short-term lags in rainfall and temperature for the occurrence of new cases of leptospirosis in Colombia.

Spatial autocorrelation and co-occurrence of six serovarieties of Leptospira in goat herds of the State of Guanajuato, Mexico

The epidemiological behavior of six Leptospira serovarieties was analyzed by spatial autocorrelation and co-occurrence of leptospirosis, diagnosed in goat herds located in the State of Guanajuato, Mexico. A total of 1650 goat serum samples were analyzed by microscopic agglutination (MAT). True prevalence (P_v) and 95% confidence interval (CI₉₅) were determined. Spatial autocorrelation was calculated using the spdep package, applying the global Moran's I and local Moran's I of Leptospira in Guanajuato. The probabilistic model of co-occurrence was applied using the co-occur package. Seroprevalence in the State was found to be 45.5% (CI₉₅ 42.96; 48.06%). The highest registered frequency was for the Icterohemorrhagiae serovar (P_v 34.16%; CI₉₅ 31.74, 36.65%), followed by the serovar Hardjo-prajitno (P_v: 6.77%; CI₉₅ 5.33, 8.40%). Other serovarieties showed a P_v < 5%. Global spatial autocorrelation, only for the Icterohemorrhagiae serovar, was I > 1, while local Moran's I revealed that five of the six Leptospira serovarieties were spatially correlated. The probabilistic model of co-occurrence detected negative associations between Icterohemorrhagiae and the other serovarieties. The current study demonstrates the presence of Leptospira in goat herds of the State of Guanajuato. The diagnosed serovarieties show an aggregation pattern associated to risk zones and disease-transmitting vectors. Antibody co-occurrence analysis revealed dominance of the Icterohemorrhagiae serovar. A multidisciplinary approach including spatial epidemiology, ecological analyses, and serological vigilance will generate useful information for the prevention and control of leptospirosis in caprine production units.

The interrelationship between meteorological parameters and leptospirosis incidence in Hambantota district, Sri Lanka 2008-2017 and practical implications

Background

Leptospirosis is a bacterial zoonosis. Leptospirosis incidence (LI) in Sri Lanka is high. Infected animals pass leptospires to the environment with their urine. Leprospires' survival in the environment to infect a new host depends on meteorological factors. El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) modulate the weather in Sri Lanka.

Objectives

The determination of interrelationship between the LI in the Hambantota District, and local meteorological parameters, ENSO and IOD.

Methods

We acquired notified leptospirosis cases in the Hambantota District and population data. We calculated weekly leptospirosis incidences for 2008 to 2017.Weather data from two weather stations was obtained, averaged and converted into weekly data. We plotted time series graphs and observed the correlation between seven aggregated weather parameters and LI. We estimated cross-correlations between those weather parameters and LI. As our principal analysis we determined correlation between LI and seven local weather parameters, Nino 3.4, Nino4 and Dipole Mode Index (DMI) indices using wavelet analysis.

Results

Our wavelet analysis results showed troughs of minimum, maximum, mean temperatures, soil temperature, the evaporation rate, the duration of sunshine were followed by peaks in LI and peaks of rainfall followed by peaks of LI, all after lag periods. Our time series graphs and cross-correlation determination results are generally in agreement with these results. However there was no significant correlation between rainfall and LI in the cross-correlation analysis. There were peaks of LI following both peaks and troughs of DMI. There was no clear correlation between both Nino indices and LI.

Discussion

This may be the first long-term study demonstrating soil temperature, evaporation rate and IOD are correlating with LI. The correlation pattern of LI with temperature parameters differs from similar past studies and we explain the reasons. We propose ways to control high LI we observed after periods of weather favorable for transmission of leptospirosis.

The effects of flooding and weather conditions on leptospirosis transmission in Thailand

The epidemic of leptospirosis in humans occurs annually in Thailand. In this study, we have developed mathematical models to investigate transmission dynamics between humans, animals, and a contaminated environment. We compared different leptospire transmission models involving flooding and weather conditions, shedding and multiplication rate in a contaminated environment. We found that the model in which the transmission rate depends on both flooding and temperature, best-fits the reported human data on leptospirosis in Thailand. Our results indicate that flooding strongly contributes to disease transmission, where a high degree of flooding leads to a higher number of infected individuals. Sensitivity analysis showed that the transmission rate of leptospires from a contaminated environment was the most important parameter for the total number of human cases. Our results suggest that public education should target people who work in contaminated environments to prevent Leptospira infections.

Leptospirosis: Increasing importance in developing countries

Leptospirosis is a zoonotic disease caused by the pathogenic helical spirochetes, Leptospira. Symptoms include sudden-onset fever, severe headaches, muscle pain, nausea and chills. Leptospirosis is endemic in developing countries such as Malaysia, India, Sri Lanka, and Brazil where thousands of cases are reported annually. The disease risk factors include the high population of reservoirs, environmental factors, recreational factors, and occupational factors. To end the endemicity of leptospirosis, these factors need to be tackled. The management of leptospirosis needs to be refined. Early diagnosis remains a challenge due to a lack of clinical suspicion among physicians, its non-specific symptoms and a limited availability of rapid point-of-care diagnostic tests. The purpose of this review is to provide insight into the status of leptospirosis in developing countries focusing on the risk factors and to propose methods for the improved management of the disease.

Hydroclimatic drivers of highly seasonal leptospirosis incidence suggest prominent soil reservoir of pathogenic Leptospira spp. in rural western China

Climate exerts complex influences on leptospirosis transmission, affecting human behavior, zoonotic host population dynamics, and survival of the pathogen in the environment. Here, we describe the spatiotemporal distribution of leptospirosis incidence reported to China’s National Infectious Disease Surveillance System from 2004–2014 in an endemic region in western China, and employ distributed lag models at annual and sub-annual scales to analyze its association with hydroclimatic risk factors and explore evidence for the potential role of a soil reservoir in the transmission of Leptospira spp. More than 97% of the 2,934 reported leptospirosis cases occurred during the harvest season between August and October, and most commonly affected farmers (83%). Using a distributed lag Poisson regression framework, we characterized incidence rate ratios (IRRs) associated with interquartile range increases in precipitation of 3.45 (95% confidence interval 2.57–4.64) over 0-1-year lags, and 1.90 (1.18–3.06) over 0-15-week lags. Adjusting for soil moisture decreased IRRs for precipitation at both timescales (yearly adjusted IRR: 1.05, 0.74–1.49; weekly adjusted IRR: 1.36, 0.72–2.57), suggesting precipitation effects may be mediated through soil moisture. Increased soil moisture was positively associated with leptospirosis at both timescales, suggesting that the survival of pathogenic Leptospira spp. in moist soils may be a critical control on harvest-associated leptospirosis transmission in the study region. These results support the hypothesis that soils may serve as an environmental reservoir and may play a significant yet underrecognized role in leptospirosis transmission.

Leptospirosis is among the leading causes of morbidity from zoonotic infections worldwide, affecting populations that are exposed to contaminated water. The disease is caused by Leptospira spp. bacteria, which are transmitted to humans either through direct contact with infected animals, or indirectly through the environment. Climatic conditions can influence transmission by altering human exposure, animal host population dynamics, and environmental conditions that allow Leptospira spp. to persist in the environment (e.g., moist environments, warm temperatures). Here, we investigated the spatiotemporal distribution of leptospirosis cases in a rural setting in western China and estimated the association between hydroclimatic conditions and leptospirosis incidence. We found that incidence of leptospirosis—especially high amongst farmers—may be associated with rice harvest, and modulated by prior bacterial accumulation within the soil under moist conditions. These results corroborate previous findings that soils may be underrecognized environmental reservoirs of pathogenic Leptospira spp., and that their role in explaining leptospirosis incidence should be considered when developing prevention programs.

The correlation between local weather and leptospirosis incidence in Kandy district, Sri Lanka from 2006 to 2015

Background: Leptospirosis is an important public health problem in Sri Lanka. Most people become infected by contact with leptospires in soil and in surface water. Survival of leptospires in the environment depends upon the moisture in soil, humidity, temperature and surface water. Leptospires are spread by flood water and waterways. Therefore, the weather of an area influences the leptospirosis incidence of that area. Objectives: To find out the correlations between the leptospirosis incidence in the district of Kandy, Sri Lanka, and local weather variables and then to explore the utility of the findings. Methods: We gathered data on reported leptospirosis cases in the Kandy district and mid-year population data and calculated weekly incidences for 2006 to 2015. Daily weather data from Katugastota weather station was obtained and converted into weekly data. We plotted time series graphs and observed the correlation between six aggregated weather parameters and leptospirosis incidence. Those weather parameters were rainfall, the count of wet days per week, days with rainfall >100 mm per week, minimum temperature, average temperature and average humidity. Then we looked for correlations between leptospirosis incidence and those weather parameters by performing the wavelet analysis. Results: Our wavelet analysis results show peaks of wet days per week, days with rainfall >100 mm per week, minimum temperature, average temperature and average humidity respectively after 2, 3, 13, 20 and 1 week lags were followed by peaks of leptospirosis incidence. Nadirs (troughs) of rainfall after a week were followed by nadirs of leptospirosis incidence. Conclusions: All weather parameters studied are correlated with local leptospirosis incidence and the climate in Kandy is conducive for leptospirosis transmission. Leptospirosis incidence in the Kandy district is high compared to the national and global incidence. Therefore, leptospirosis preventive work in Kandy deserves more attention, especially during months with favorable weather for leptospirosis transmission. Video abstract Read the transcript Watch the video on Vimeo.

Climate variability, satellite-derived physical environmental data and human leptospirosis: A retrospective ecological study in China

BACKGROUND

In the past three decades, the incidence rate of notified leptospirosis cases in China have steeply declined and are now circumscribed to discrete areas in the country. Previous research showed that climate and environmental variation may play an important role in leptospirosis transmission. However, quantitative associations between climate, environmental factors and leptospirosis in the high-risk areas in China, is still poorly understood.

OBJECTIVE

To quantify the temporal effects of climate and remotely-sensed physical environmental factors on human leptospirosis in the high-risk counties in China.

METHODS

Time series seasonal decomposition was performed to explore the seasonality pattern of leptospirosis incidence in Mengla County, Yunnan and Yilong County, Sichuan for the period 2006-2016. Time series cross-correlation analysis was carried out to examine lagged effects of rainfall, relative humidity, normalized difference vegetation index (NDVI), modified normalized difference water index (MNDWI) and land surface temperature (LST) on leptospirosis. The associations of climatic and physical environment factors with leptospirosis in each county were assessed by using a generalized linear regression model with negative binomial link, adjusted by seasonal components.

RESULTS

Leptospirosis incidence in both counties showed strong and unique annual seasonality. Our results show that in Mengla County leptospirosis notifications exhibits a bi-modal temporal pattern while in Yilong County it follows a typical single epidemic curve. After adjusting for seasonality, the final best-fitting model for Mengla County indicated that leptospirosis notifications were significantly associated with present LST values (incidence rate ratio, IRR = 0.857, 95% confidence interval (CI):0.729-0.929) and rainfall at a lag of 6-months (IRR = 0.989; 95% CI: 0.985-0.993). The incidence of leptospirosis in Yilong was associated with rainfall at 1-month lag (IRR = 1.013, 95% CI: 1.003-1.023), LST (3-months lag) (IRR = 1.193, 95% CI: 1.095-1.301), and MNDWI (5-months lag) (IRR = 7.960, 95% CI: 1.241-47.66).

CONCLUSIONS

Our study identified lagged effects between leptospirosis incidence and climate and remotely-sensed environmental factors in the two most endemic counties in China. Rainfall in combination with satellite derived physical environment factors provided better insight of the local epidemiology as well as good predictors for leptospirosis outbreak in both counties. This would also be an avenue for the development of leptospirosis early warning systems to support leptospirosis control in China.

Spatial epidemiological approaches to inform leptospirosis surveillance and control: A systematic review and critical appraisal of methods

Leptospirosis is a global zoonotic disease that the transmission is driven by complex geographical and temporal variation in demographics, animal hosts and socioecological factors. This results in complex challenges for the identification of high-risk areas. Spatial and temporal epidemiological tools could be used to support leptospirosis control programs, but the adequacy of its application has not been evaluated. We searched literature in six databases including PubMed, Web of Science, EMBASE, Scopus, SciELO and Zoological Record to systematically review and critically assess the use of spatial and temporal analytical tools for leptospirosis and to provide general framework for its application in future studies. We reviewed 115 articles published between 1930 and October 2018 from 41 different countries. Of these, 65 (56.52%) articles were on human leptospirosis, 39 (33.91%) on animal leptospirosis and 11 (9.5%) used data from both human and animal leptospirosis. Spatial analytical (n = 106) tools were used to describe the distribution of incidence/prevalence at various geographical scales (96.5%) and to explored spatial patterns to detect clustering and hot spots (33%). A total of 51 studies modelled the relationships of various variables on the risk of human (n = 31), animal (n = 17) and both human and animal infection (n = 3). Among those modelling studies, few studies had generated spatially structured models and predictive maps of human (n = 2/31) and animal leptospirosis (n = 1/17). In addition, nine studies applied time-series analytical tools to predict leptospirosis incidence. Spatial and temporal analytical tools have been greatly utilized to improve our understanding on leptospirosis epidemiology. Yet the quality of the epidemiological data, the selection of covariates and spatial analytical techniques should be carefully considered in future studies to improve usefulness of evidence as tools to support leptospirosis control. A general framework for the application of spatial analytical tools for leptospirosis was proposed.

A remotely sensed flooding indicator associated with cattle and buffalo leptospirosis cases in Thailand 2011-2013

BACKGROUND

Leptospirosis is an important zoonotic disease worldwide, caused by spirochetes bacteria of the genus Leptospira. In Thailand, cattle and buffalo used in agriculture are in close contact with human beings. During flooding, bacteria can quickly spread throughout an environment, increasing the risk of leptospirosis infection. The aim of this study was to investigate the association of several environmental factors with cattle and buffalo leptospirosis cases in Thailand, with a focus on flooding.

METHOD

A total of 3571 urine samples were collected from cattle and buffalo in 107 districts by field veterinarians from January 2011 to February 2013. All samples were examined for the presence of leptospirosis infection by loop-mediated isothermal amplification (LAMP). Environmental data, including rainfall, percentage of flooded area (estimated by remote sensing), average elevation, and human and livestock population density were used to build a generalized linear mixed model.

RESULTS

A total of 311 out of 3571 (8.43%) urine samples tested positive by the LAMP technique. Positive samples were recorded in 51 out of 107 districts (47.66%). Results showed a significant association between the percentage of the area flooded at district level and leptospirosis infection in cattle and buffalo (p = 0.023). Using this data, a map with a predicted risk of leptospirosis can be developed to help forecast leptospirosis cases in the field.

CONCLUSIONS

Our model allows the identification of areas and periods when the risk of leptospirosis infection is higher in cattle and buffalo, mainly due to a seasonal flooding. The increased risk of leptospirosis infection can also be higher in humans too. These areas and periods should be targeted for leptospirosis surveillance and control in both humans and animals.

The non-linear and lagged short-term relationship between rainfall and leptospirosis and the intermediate role of floods in the Philippines

Background

Leptospirosis is a worldwide bacterial zoonosis. Outbreaks of leptospirosis after heavy rainfall and flooding have been reported. However, few studies have formally quantified the effect of weather factors on leptospirosis incidence. We estimated the association between rainfall and leptospirosis cases in an urban setting in Manila, the Philippines, and examined the potential intermediate role of floods in this association.

Methods/Principal findings

Relationships between rainfall and the weekly number of hospital admissions due to leptospirosis from 2001 to 2012 were analyzed using a distributed lag non-linear model in a quasi-Poisson regression framework, controlling for seasonally varying factors other than rainfall. The role of floods on the rainfall–leptospirosis relationship was examined using an indicator. We reported relative risks (RRs) by rainfall category based on the flood warning system in the country. The risk of post-rainfall leptospirosis peaked at a lag of 2 weeks (using 0 cm/week rainfall as the reference) with RRs of 1.30 (95% confidence interval: 0.99–1.70), 1.53 (1.12–2.09), 2.45 (1.80–3.33), 4.61 (3.30–6.43), and 13.77 (9.10–20.82) for light, moderate, heavy, intense and torrential rainfall (at 2, 5, 16, 32 and 63 cm/week), respectively. After adjusting for floods, RRs (at a lag of 2 weeks) decreased at higher rainfall levels suggesting that flood is on the causal pathway between rainfall and leptospirosis.

Conclusions

Rainfall was strongly associated with increased hospital admission for leptospirosis at a lag of 2 weeks, and this association was explained in part by floods.

Leptospirosis is a worldwide bacterial zoonosis which is mainly transmitted through contact with water contaminated by rodents’ urine. It manifests with various symptoms, ranging from fever and muscle pain to a severe syndrome characterized by jaundice, renal failure and pulmonary hemorrhage. Outbreaks of leptospirosis after heavy rainfall and flooding have been reported, but few studies have evaluated the effect of weather factors on leptospirosis. We estimated the association between rainfall and leptospirosis cases in an urban setting in Manila, the Philippines, and examined the potential intermediate role of floods in this association. The risk of post-rainfall leptospirosis peaked at a lag of 2 weeks. After adjusting for floods, the effect of rainfall at lag 2 decreased at higher rainfall levels suggesting that flooding is on the causal pathway between heavy rainfall and leptospirosis. The results are useful for public health interventions to prepare hospitals and clinics for increased number of patients in case of an outbreak, which can help reduce the disease burden.

Leptospirosis Outbreak After the 2014 Major Flooding Event in Kelantan, Malaysia: A Spatial-Temporal Analysis

Severe floods increase the risk of leptospirosis outbreaks in endemic areas. This study determines the spatial-temporal distribution of leptospirosis in relation to environmental factors after a major flooding event in Kelantan, Malaysia. We conducted an observational ecological study involving incident leptospirosis cases, from the 3 months before, during, and three months after flood, in reference to the severe 2014 Kelantan flooding event. Geographical information system was used to determine the spatial distribution while climatic factors that influenced the cases were also analyzed. A total of 1,229 leptospirosis cases were notified within the three study periods where incidence doubled in the postflood period. Twelve of 66 subdistricts recorded incidence rates of over 100 per 100,000 population in the postflood period, in comparison with only four subdistricts in the preflooding period. Average nearest neighborhood analysis indicated that the cases were more clustered in the postflood period as compared with the preflood period, with observed mean distance of 1,139 meters and 1,666 meters, respectively (both at P < 0.01). Global Moran's I was higher in the postflood period (0.19; P < 0.01) as compared with the preflood period (0.06; P < 0.01). Geographic weighted regression showed that living close to water bodies increased the risk of contracting the disease. Postflooding hotspots were concentrated in areas where garbage cleanup occurred and the incidence was significantly associated with temperature, humidity, rainfall, and river levels. Postflooding leptospirosis outbreak was associated with several factors. Understanding the spatial distribution and associated factors of leptospirosis can help improve future disease outbreak management after the floods.

The influence of climatic factors on the development of hemorrhagic fever with renal syndrome and leptospirosis during the peak season in Korea: an ecologic study

BACKGROUND

Hemorrhagic fever with renal syndrome (HFRS) and leptospirosis are seasonal rodent-borne infections in the Republic of Korea (Korea). The occurrences of HFRS and leptospirosis are influenced by climatic variability. However, few studies have examined the effects of local climatic variables on the development of these infections. The purpose of this study was to estimate the effect of climatic factors on the occurrence of HFRS and leptospirosis in Korea.

METHODS

Daily records on human cases of HFRS and leptospirosis between January 2001 to December 2009 were analyzed. The associations of climatic factors with these cases in high incidence provinces were estimated using the time-series method and multivariate generalized linear Poisson models with a maximal lag of 12 weeks.

RESULTS

From 2001 to 2009, a total of 2912 HFRS and 889 leptospirosis cases were reported, with overall incidences of 0.67 and 0.21 cases per 100,000, respectively, in the study areas. The increase in minimum temperature (1 °C) at a lag of 11 weeks was associated with 17.8% [95% confidence interval (CI): 15.1, 20.6%] and 22.7% (95% CI: 16.5, 29.3%) increases in HFRS and leptospirosis cases, respectively. A 1-h increase in the daily sunshine was related to a 27.5% (95% CI: 18.2, 37.6%) increase in HFRS at a lag of 0 week. A 1% increase in daily minimum relative humidity and a 1 mm increase in daily rainfall were associated with 4.0% (95% CI:1.8, 6.1) and 2.0% (95% CI: 1.2, 2.8%) increases in weekly leptospirosis cases at 11 and 6 weeks later, respectively. A 1 mJ/m² increase in daily solar radiation was associated with a 13.7% (95% CI: 4.9, 23.2%) increase in leptospirosis cases, maximized at a 2-week lag.

CONCLUSIONS

During the peak season in Korea, climatic factors play a significant role in the development of HFRS and leptospirosis. The findings of this study may be applicable to the forecasting and prediction of disease outbreaks.

Leptospirosis: risk factors and management challenges in developing countries

Leptospirosis is a widespread bacterial zoonosis with highest burden in low-income populations living in tropical and subtropical regions, both in urban and in rural environments. Rodents are known as the main reservoir animals, but other mammals may also significantly contribute to human infections in some settings. Clinical presentation of leptospirosis is nonspecific and variable, and most of the early signs and symptoms point to the so-called “acute fever of unknown origin”, a major diagnostic challenge in tropical and subtropical areas. However, leptospirosis can rapidly evolve to life-threatening complications, especially if left untreated. There is a need for good awareness of leptospirosis and rapid antibiotic treatment based on clinical and epidemiological suspicion. Severe leptospirosis cases include renal and/or respiratory failure and shock, necessitating intensive care, also seldom available or with limited capacity. Confirmation of leptospirosis relies on biological diagnosis, which unfortunately uses tricky methods seldom available. This biological confirmation, however, is essential for surveillance and public health purpose. A good knowledge of leptospirosis epidemiology (eg, the reservoir animals involved, the Leptospira strains circulating, the seasonal and geographical patterns, and specific populations at risk) can be achieved through adequate surveillance and diagnosis. This can pave the way to prevention and intervention strategies and in turn alleviate the toll leptospirosis takes on affected populations. Over the past few years, leptospirosis has been increasingly recognized, as the need for multidisciplinary approaches in a One-Health perspective has been acknowledged, raising hope to successfully tackle the challenges of this zoonosis.

Towards a geocomputational landscape epidemiology: surveillance, modelling, and interventions

The ability to explicitly represent infectious disease distributions and their risk factors over massive geographical and temporal scales has transformed how we investigate how environment impacts health. While landscape epidemiology studies have shed light on many aspects of disease distribution and risk differentials across geographies, new computational methods combined with new data sources such as citizen sensors, global spatial datasets, sensor networks, and growing availability and variety of satellite imagery offer opportunities for a more integrated approach to understanding these relationships. Additionally, a large number of new modelling and mapping methods have been developed in recent years to support the adoption of these new tools. The complexity of this research context results in study-dependent solutions and prevents landscape approaches from deeper integration into operational models and tools. In this paper we consider three common research contexts for spatial epidemiology; surveillance, modelling to estimate a spatial risk distribution and the need for intervention, and evaluating interventions and improving healthcare. A framework is proposed and a categorization of existing methods is presented. A case study into leptospirosis in Sri Lanka provides a working example of how the different phases of the framework relate to real research problems. The new framework for geocomputational landscape epidemiology encompasses four key phases: characterizing assemblages, characterizing functions, mapping interdependencies, and examining outcomes. Results from Sri Lanka provide evidence that the framework provides a useful way to structure and interpret analyses. The framework reported here is a new way to structure existing methods and tools of geocomputation that are increasingly relevant to researchers working on spatially explicit disease-landscape studies.

The panorama of animal leptospirosis in Rio de Janeiro, Brazil, regarding the seroepidemiology of the infection in tropical regions

Background

Leptospirosis is an important disease caused by various serovars of Leptospira sp. It can affect humans as well as domestic and wild animals; therefore, it has importance for public health, animal production, and wild species. The aim of this paper is to discuss the epidemiology of animal leptospirosis in Rio de Janeiro, Brazil, as a possible model for other tropical regions. In several studies conducted in the last 20 years, a total of 47 rats, 120 dogs, 875 cows, 695 horses, 1,343 goats, 308 sheep and 351 pigs from all regions of the state, in addition to 107 wild mammals and 73 golden-lion tamarins were tested (MAT) for anti-Leptospira antibodies.

Results

Seroreactivity was frequent in all studied species, confirming that the infection is endemic in Rio de Janeiro. Serogroups Icterohaemorrhagiae and Sejroe were the most prevalent in urban and rural scenarios, respectively. This paper reviews the current knowledge on animal leptospirosis in Rio de Janeiro and describes important differences between urban versus rural cycles of the infection in various species.

Conclusion

Identification of the prevailing serogroups and their reservoirs is essential for understanding agent-host-environment interactions under tropical conditions.

Leptospirosis in the republic of Korea: historical perspectives, current status and future challenges

Leptospirosis is an important public health problem in the Republic of Korea (ROK), occurring sporadically or in outbreaks during the autumn season. Wild rodents, Apodemus agrarius, have been mainly involved in human leptospirosis. The majority of carrier animals are infected with Leptospira interrogans serovar lai. The characteristic pulmonary involvement or hemorrhage may increase the clinical severity or result in fatal outcomes, and these aspects continue to be a threat to people in endemic areas. While the disease incidence has been relatively low in recent years, there have been newer findings of livestock (zoo animals and racing horses) and rats (Rattus norvegicus) captured in urban environments as potential animal carriers. Many avenues of research are still open to define current changes in ecology, epidemiology, and the disease burden in both humans and animals in the ROK, together with global warming and climate change issues. In addition, national policy regarding the weighted wildlife monitoring system and the enhanced disease surveillance program is required to facilitate better monitoring and understanding of this disease.