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

Analysing the outbreaks of leptospirosis after floods in Kerala, India

A growing number of studies have linked the incidence of leptospirosis with the occurrence of flood events. Nevertheless, the interaction between flood and leptospirosis has not been extensively studied to understand the influence of flood attributes in inducing new cases. This study reviews leptospirosis cases in relation to multiple flood occurrences in Kerala, India. Leptospirosis data were obtained for three years: 2017 (non-flood year) and two years with flooding-2018 (heavy flooding) and 2019 (moderate flooding). We considered the severity of flood events using the discharge, duration and extent of each flooding event and compared them with the leptospirosis cases. The distribution of cases regarding flood discharge and duration was assessed through descriptive and spatiotemporal analyses, respectively. Furthermore, cluster analyses and spatial regression were completed to ascertain the relationship between flood extent and the postflood cases. This study found that postflood cases of leptospirosis can be associated with flood events in space and time. The total cases in both 2018 and 2019 increased in the post-flood phase, with the increase in 2018 being more evident. Unlike the 2019 flood, the flood of 2018 is a significant spatial indicator for postflood cases. Our study shows that flooding leads to an increase in leptospirosis cases, and there is stronger evidence for increased leptospirosis cases after a heavy flood event than after a moderate flooding event. Flood duration may be the most important factor in determining the increase in leptospirosis infections.

Spatiotemporal assessment of pathogenic Leptospira in subtropical coastal watersheds

The World Health Organization classifies leptospirosis as a significant public health concern, predominantly affecting impoverished and unsanitary regions. By using the Pensacola Bay System as a case study, this study examines the underappreciated susceptibility of developed subtropical coastal ecosystems such as the Pensacola Bay System to neglected zoonotic pathogens such as Leptospira. We analyzed 132 water samples collected over 12 months from 44 distinct locations with high levels of Escherichia coli (>410 most probable number/100 mL). Fecal indicator bacteria (FIB) concentrations were assessed using IDEXX Colilert-18 and Enterolert-18, and an analysis of water physiochemical characteristics and rainfall intensity was conducted. The LipL32 gene was used as a quantitative polymerase chain reaction (qPCR) indicator to identify the distribution of Leptospira interrogans. The results revealed 12 instances of the presence of L. interrogans at sites with high FIB over various land cover and aquatic ecosystem types. Independent of specific rainfall events, a seasonal relationship between precipitation and elevated rates of fecal bacteria and leptospirosis was found. These findings highlight qPCR's utility in identifying pathogens in aquatic environments and the widespread conditions where it can be found in natural and developed areas.

An investigation of geographical clusters of leptospirosis during the outbreak in Pangandaran, West Java, Indonesia

Leptospirosis is neglected in many tropical developing countries, including Indonesia. Our research on this zoonotic disease aimed to investigate epidemiological features and spatial clustering of recent leptospirosis outbreaks in Pangandaran, West Java. The study analysed data on leptospirosis notifications between September 2022 and May 2023. Global Moran I and local indicator for spatial association (LISA) were applied. Comparative analysis was performed to characterise the identified hotspots of leptospirosis relative to its neighbourhoods. A total of 172 reported leptospirosis in 40 villages from 9 sub-districts in Pangandaran District were analysed. Of these, 132 cases (76.7%) were male. The median age was 49 years (interquartile range [IQR]: 34-59 years). Severe outcomes including renal failure, lung failure, and hepatic necrosis were reported in up to 5% of the cases. A total of 30 patients died, resulting in the case fatality rate (CFR) of 17.4%. Moran's I analysis showed significant spatial autocorrelation (I=0.293; p=0.002) and LISA results identified 7 High-High clusters (hotspots) in the Southwest, with the total population at risk at 26,184 people. The hotspots had more cases among older individuals (median age: 51, IQR: 36-61 years; p<0.001), more farmers (79%, p=0.001) and more evidence of the presence of rats (p=0.02). A comprehensive One Health intervention should be targeted towards these high-risk areas to control the transmission of leptospirosis. More empirical evidence is needed to understand the role of climate, animals and sociodemographic characteristics on the transmission of leptospirosis in the area studied.

Leptospirosis modelling using hydrometeorological indices and random forest machine learning

Leptospirosis is a zoonosis that has been linked to hydrometeorological variability. Hydrometeorological averages and extremes have been used before as drivers in the statistical prediction of disease. However, their importance and predictive capacity are still little known. In this study, the use of a random forest classifier was explored to analyze the relative importance of hydrometeorological indices in developing the leptospirosis model and to evaluate the performance of models based on the type of indices used, using case data from three districts in Kelantan, Malaysia, that experience annual monsoonal rainfall and flooding. First, hydrometeorological data including rainfall, streamflow, water level, relative humidity, and temperature were transformed into 164 weekly average and extreme indices in accordance with the Expert Team on Climate Change Detection and Indices (ETCCDI). Then, weekly case occurrences were classified into binary classes "high" and "low" based on an average threshold. Seventeen models based on "average," "extreme," and "mixed" indices were trained by optimizing the feature subsets based on the model computed mean decrease Gini (MDG) scores. The variable importance was assessed through cross-correlation analysis and the MDG score. The average and extreme models showed similar prediction accuracy ranges (61.5-76.1% and 72.3-77.0%) while the mixed models showed an improvement (71.7-82.6% prediction accuracy). An extreme model was the most sensitive while an average model was the most specific. The time lag associated with the driving indices agreed with the seasonality of the monsoon. The rainfall variable (extreme) was the most important in classifying the leptospirosis occurrence while streamflow was the least important despite showing higher correlations with leptospirosis.

Linking rattiness, geography and environmental degradation to spillover Leptospira infections in marginalised urban settings: An eco-epidemiological community-based cohort study in Brazil

Background

Zoonotic spillover from animal reservoirs is responsible for a significant global public health burden, but the processes that promote spillover events are poorly understood in complex urban settings. Endemic transmission of Leptospira, the agent of leptospirosis, in marginalised urban communities occurs through human exposure to an environment contaminated by bacteria shed in the urine of the rat reservoir. However, it is unclear to what extent transmission is driven by variation in the distribution of rats or by the dispersal of bacteria in rainwater runoff and overflow from open sewer systems.

Methods

We conducted an eco-epidemiological study in a high-risk community in Salvador, Brazil, by prospectively following a cohort of 1401 residents to ascertain serological evidence for leptospiral infections. A concurrent rat ecology study was used to collect information on the fine-scale spatial distribution of 'rattiness', our proxy for rat abundance and exposure of interest. We developed and applied a novel geostatistical framework for joint spatial modelling of multiple indices of disease reservoir abundance and human infection risk.

Results

The estimated infection rate was 51.4 (95%CI 40.4, 64.2) infections per 1000 follow-up events. Infection risk increased with age until 30 years of age and was associated with male gender. Rattiness was positively associated with infection risk for residents across the entire study area, but this effect was stronger in higher elevation areas (OR 3.27 95% CI 1.68, 19.07) than in lower elevation areas (OR 1.14 95% CI 1.05, 1.53).

Conclusions

These findings suggest that, while frequent flooding events may disperse bacteria in regions of low elevation, environmental risk in higher elevation areas is more localised and directly driven by the distribution of local rat populations. The modelling framework developed may have broad applications in delineating complex animal-environment-human interactions during zoonotic spillover and identifying opportunities for public health intervention.

Funding

This work was supported by the Oswaldo Cruz Foundation and Secretariat of Health Surveillance, Brazilian Ministry of Health, the National Institutes of Health of the United States (grant numbers F31 AI114245, R01 AI052473, U01 AI088752, R01 TW009504 and R25 TW009338); the Wellcome Trust (102330/Z/13/Z), and by the Fundação de Amparo à Pesquisa do Estado da Bahia (FAPESB/JCB0020/2016). MTE was supported by a Medical Research UK doctorate studentship. FBS participated in this study under a FAPESB doctorate scholarship.

Determining the spatial distribution of environmental and socio-economic suitability for human leptospirosis in the face of limited epidemiological data

Background

Leptospirosis is among the leading zoonotic causes of morbidity and mortality worldwide. Knowledge about spatial patterns of diseases and their underlying processes have the potential to guide intervention efforts. However, leptospirosis is often an underreported and misdiagnosed disease and consequently, spatial patterns of the disease remain unclear. In the absence of accurate epidemiological data in the urban agglomeration of Santa Fe, we used a knowledge-based index and cluster analysis to identify spatial patterns of environmental and socioeconomic suitability for the disease and potential underlying processes that shape them.

Methods

We geocoded human leptospirosis cases derived from the Argentinian surveillance system during the period 2010 to 2019. Environmental and socioeconomic databases were obtained from satellite images and publicly available platforms on the web. Two sets of human leptospirosis determinants were considered according to the level of their support by the literature and expert knowledge. We used the Zonation algorithm to build a knowledge-based index and a clustering approach to identify distinct potential sets of determinants. Spatial similarity and correlations between index, clusters, and incidence rates were evaluated.

Results

We were able to geocode 56.36% of the human leptospirosis cases reported in the national epidemiological database. The knowledge-based index showed the suitability for human leptospirosis in the UA Santa Fe increased from downtown areas of the largest cities towards peri-urban and suburban areas. Cluster analysis revealed downtown areas were characterized by higher levels of socioeconomic conditions. Peri-urban and suburban areas encompassed two clusters which differed in terms of environmental determinants. The highest incidence rates overlapped areas with the highest suitability scores, the strength of association was low though (CSc r = 0.21, P < 0.001 and ESc r = 0.19, P < 0.001).

Conclusions

We present a method to analyze the environmental and socioeconomic suitability for human leptospirosis based on literature and expert knowledge. The methodology can be thought as an evolutive and perfectible scheme as more studies are performed in the area and novel information regarding determinants of the disease become available. Our approach can be a valuable tool for decision-makers since it can serve as a baseline to plan intervention measures.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40249-022-01010-x.

Spatial epidemiology of Leptospira sp. exposure in bovines from Veracruz, México

Bovine leptospirosis is a bacterial disease that affects cattle herds, causing economic losses due to reproductive problems which require expensive treatments. The main source of transmission for cattle is still uncertain, but rodents and bats can play an important role in the transmission cycle by being maintenance hosts for the pathogenic species of the bacterium and spreading it through urine. In this study, we characterize possible risk areas for bovine leptospirosis exposure in the state of Veracruz, Mexico, based on the geographical distribution of flying (bats) and terrestrial (rodents and opossums) wild hosts of Leptospira sp. reported in Mexico, in addition to climate, geography, soil characteristics, land use and human activities (environmental variables). We used a generalized linear regression model to understand the association between the frequency of anti-Leptospira sp. antibodies (a proxy of exposure) in cattle herds exposed to Leptospira, the favourability of wild hosts of Leptospira as well as the environmental variables. The parameterized model explained 12.3% of the variance. The frequency of anti-Leptospira sp. antibodies exposure in cattle herds was associated with elevation, geographic longitude, pH of the soil surface and environmental favourability for the presence of rodents, opossums and bats. The variation in exposure was mainly explained by a longitudinal gradient (6.4% of the variance) and the favourability-based indices for wild hosts (9.6% of the variance). Describing the possible risks for exposure to Leptospira in an important and neglected livestock geographical region, we provide valuable information for the selection of areas for diagnosis and prevention of this relevant disease.

Spatial distribution models of seroreactive sheep to Leptospira spp. in Veracruz, Mexico

Leptospirosis is an infectious zoonotic disease of special importance in tropical regions of the world and is closely related to climatic conditions. In Mexico, at least eight Leptospira serogroups are known to affect sheep, but little is known about their distribution. The aim was to analyze the spatial distribution of seroreactive sheep to eight serogroups of Leptospira spp. through ecological niche modeling from the state of Veracruz. We carried out a cross-sectional, multi-stage, and stratified epidemiological study, sampling 405 sheep in different regions of the state (north, center, and south). The sera were analyzed using the Microscopic Agglutination Test (MAT) to identify seropositivity to eight Leptospira serogroups (Icterohaemorrhagiae, Pyrogenes, Grippotyphosa, Canicola, Pomona, Hardjo, Wolffi, and Tarassovi). Management variables in the sampled herds were evaluated through a survey among the producers, which was analyzed using the Chi-square test for cross-tabulation. Geospatial modeling was conducted using MAXENT and 19 climatic variables and the validation was carried out using the area under the curve (AUC). No positive animals were found for Pomona in any area of Veracruz and there was only one case of seroreactivity to Grippotyphosa. The total seroprevalence found was 53.83% (95% CI: 48.84-58.75). The main serogroup found was Sejroe (55.31%, 95% CI 50.32 - 60.20%), followed by Canicola (8.64%, 95% CI 6.17 - 11.92%), Icterohaemorrhagiae (4.69%, 95% CI 2.93 - 7.36%), Tarassovi (3.95%, 95% CI 2.35 - 6.47%), Pyrogenes (2.47%, 95% CI 1.26 - 4.64%), Australis (0.99%, 95% CI 0.32 - 2.69%) and Grippotyphosa (0.25%, 95% CI 0.01 - 1.59%). The predictive model for Australis was not significant. Acceptable predictive models (AUC>0.7-0.8) were found for Canicola, Icterohaemorrhagiae, Pyrogenes, and Tarassovi; while for Sejroe it was excellent (AUC> 0.85); consequently, the climatic variables that most contributed to the model were those related to precipitation. The potential distribution of Pyrogenes, Icterohaemorrhagiae, and Canicola was located to a greater extent in the three regions; Pyrogenes and Tarassovi were distributed mostly in the north and central regions and Sejroe is mostly located in the center and south of the state. Ecological niche modeling could support epidemiological control and surveillance programs for affected sheep herds in the state of Veracruz. This article is protected by copyright. All rights reserved.

Seroprevalence and risk factors of Leptospira sp. among different groups in the Jordanian population: first study

BACKGROUND

Leptospirosis is re-emerging as a major public health problem worldwide. However, there are limited data on the disease from the Middle East, including from Jordan, despite recent outbreaks occurring in Jordan's neighbouring countries.

METHODS

Sera samples from 809 participants in 11 governorates were tested for Leptospira sp. seropositivity to determine the seroprevalence and risk factors of Leptospira sp. in Jordan.

RESULTS

Overall, 3.3% (95% confidence interval [CI] 2.2 to 4.8) of individuals tested were seropositive for Leptospira antibodies. Individuals who drink surface water (spring or rain water) had 5.69 (95% CI 2.57 to 12.60) higher odds of seropositivity compared with individuals who used municipal or filtered water, after controlling for age and practicing horticulture.

CONCLUSIONS

This is the first seroprevalence study of Leptospira sp. in Jordan and included important data on environmental and animal exposures.

Spatio-temporal distribution and agroecological factors associated with canine leptospirosis in Great Britain

Leptospirosis is an important global zoonotic disease that affects a wide range of mammalian species. Canine leptospirosis outbreaks have been reported after metereological events such as flooding (eg. in Brazil and the United States of America) suggesting an environmental association, but there has been no such study in Great Britain (GB). The distribution of cases across GB is also unreported. Objectives of this study were to: (1) assess the spatio-temporal variation of leptospirosis test submissions (2) explore associations between agroecological risk factors and distribution of different canine leptospirosis serogroups in GB, and (3) generate probability of presence maps for the different serogroups. Data analysed comprised laboratory submissions (n = 3986) to IDEXX laboratories between 1st January 2009 and 31st December 2018 for PCR or MAT leptospirosis testing. Spatial and seasonal scan statistics were used to investigate spatial and temporal clustering of positive tests, logistic regression was used to identify significant agroecological risk factors for positive tests, and the Maxent algorithm was used to model the environmental niche of four serogroups. There was an increased risk of a positive test result in the West Midlands of England (relative risk = 2.16) and between October and January (relative risk = 1.54). Logistic regression identified season and region to be significantly associated with a positive diagnosis,with higher odds of a positive test in Autumn (OR = 1.86 95 %CI 1.29-2.69) and Winter (OR = 1.51, 95 %CI 1.02-2.23) and in the East (OR = 2.20, 95 %CI = 1.31-3.71) and West Midlands (OR = 2.32, 95 %CI 1.45-3.71). The increased test-positive proportion in Autumn together with the increased odds of a positive diagnosis in Autumn suggests there may be a seasonal pattern to the canine leptospirosis in GB. The most important variable associated with higher leptospirosis presence in all ecological niche models was higher average annual temperature. The importance and retention of other variables differed between serogroups. Overall, a higher probability of leptospirosis presence was predicted in southern England and a low probability in Scotland and northern England. Although leptospirosis vaccine usage provides protection against the majority of serogroups identified here, one is not represented in the currently licensed vaccine formulations and therefore leptospirosis should remain a differential diagnosis in vaccinated dogs demonstrating consistent clinical signs of the disease.

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.

Seroepidemiology of Leptospira infection in slaughtered cattle in Gauteng province, South Africa

Leptospirosis is an important economical disease of livestock globally, especially in Asia, the Caribbean, and the African continent. Its presence has been reported in a wide range of livestock. However, information on leptospirosis in South Africa is scanty. We conducted a cross-sectional study in 11 randomly selected abattoirs to determine the seroprevalence and risk factors for leptospirosis in slaughtered cattle in Gauteng province, South Africa. During abattoir visits to selected abattoirs, blood samples were collected from 199 cattle and demographic data obtained on the slaughtered animals. The microscopic agglutination test (MAT) was performed on all sera using a 26-serotype panel using cutoff titer ≥ 1:100. Animal- and abattoir-level risk factors were investigated for their association with seropositivity for leptospirosis. The seroprevalence of leptospirosis in the cattle sampled was 27.6% (55/199). The predominant serogroups detected in seropositive cattle were Sejroe (sv. Hardjo) (38.2%) and Mini sv. Szwajizak) (14.5%) but low to Canicola (sv. Canicola) (1.8%) and Pomona (sv. Pomona) (1.8%). The differences were statistically significant (P < 0.05). Of the five variables investigated, only one (abattoirs) had statistically significantly (P < 0.001) differences in the seroprevalence of leptospirosis among abattoirs. The study documented for the first time in South Africa, the occurrence of serogroups Sejroe (Hardjo bovis strain lely 607), Tarassovi, Hebdomadis, and Medanensis in slaughtered cattle. It was concluded that six of the nine serovars (representing seven serogroups) of Leptospira spp. circulating in cattle population in South Africa are not vaccine serogroups. The clinical, diagnostic, and public health importance of the findings cannot be ignored.

Interactive web-based tool for evaluating the spread of bovine tuberculosis and brucellosis in Colombia

Background: Bovine tuberculosis (BTB) and brucellosis are associated with devastating losses in the livestock sector in Colombia and even in developed countries. Real-time disease surveillance is a key strategy to control and eradicate infectious disease outbreaks. Objective: To design an epidemiological tool for monitoring BTB and brucellosis in Colombia. Methods: An interactive platform for disease mapping of BTB and brucellosis during an observation period between years 2004 and 2019 was designed. Results: Our analysis showed that the provinces of Cundinamarca and Valle del Cauca are regions affected by BTB and brucellosis epidemics, respectively (p<0.001). Furthermore, increased case detection of BTB was reported in 2012 and brucellosis in 2019 (p<0.001). Conclusions: This epidemiological platform allows tracking BTB and tuberculosis hotspots, identifying trends over time, and provides useful information to animal health authorities for designing new strategies in control programs.

Spatial distribution of leptospirosis incidence in the Upper Yangtze and Pearl River Basin, China: Tools to support intervention and elimination

BACKGROUND

Since 2011 human leptospirosis incidence in China has remained steadily low with persistent pockets of notifications reported in communities within the Upper Yangtze River Basin (UYRB) and Pearl River Basin (PRB). To help guide health authorities within these residual areas to identify communities where interventions should be targeted, this study quantified the local effect of socioeconomic and environmental factors on the spatial distribution of leptospirosis incidence and developed predictive maps of leptospirosis incidence for UYRB and PRB.

METHODS

Data on all human leptospirosis cases reported during 2005-2016 across the UYRB and PRB regions were geolocated at the county-level and included in the analysis. Bayesian conditional autoregressive (CAR) models with zero-inflated Poisson link for leptospirosis incidence were developed after adjustment of environmental and socioeconomic factors such as precipitation, normalized difference vegetation index (NDVI), modified normalized difference water index (MNDWI), land surface temperature (LST), elevation, slope, land cover, crop production, livestock density, gross domestic product and population density.

RESULTS

The relationship of environmental and socioeconomic variables with human leptospirosis incidence varied between both regions. While across UYRB incidence of human leptospirosis was associated with MNDWI and elevation, in PRB human leptospirosis incidence was significantly associated with NDVI, livestock density and land cover. Precipitation was significantly and positively associated with the spatial variation of incidence of leptospirosis in both regions. After accounting for the effect of environmental and socioeconomic factors, the predicted distribution of residual high-incidence county is potentially more widespread both in the UYRB and PRB compared to the observed distribution. In the UYRB, the highest predicted incidence was found along the border of Chongqing and Guizhou towards Sichuan basin and northwest Yunnan. The highest predicted incidence was also identified in counties in the central and lower reaches of the PRB.

CONCLUSIONS

This study demonstrated significant geographical heterogeneity in leptospirosis incidence within UYRB and PRB, providing an evidence base for prioritising targeted interventions in counties identified with the highest predicted incidence. Furthermore, environmental drivers of leptospirosis incidence were highly specific to each of the regions, emphasizing the importance of localized control measures. The findings also suggested the need to expand interventional coverage and to support surveillance and diagnostic capacity on the predicted high-risk areas.

Environmental Risk of Leptospirosis in Animals: The Case of The Republic of Sakha (Yakutia), Russian Federation

Leptospirosis is a zoonotic natural focal disease caused by the pathogenic bacteria Leptospira. Its spread is related to certain ecological factors. The aim of the current research was to assess potential exposure to the infection as a function of environmental determinants in the Republic of Sakha (Yakutia), Russian Federation. We applied environmental niche modeling using leptospirosis cases in livestock and wild animals in 1995–2019 with regard to a set of landscape, climatic, and socioeconomic variables, both for the current climate and for the projected climate for 2041–2060. The MaxEnt model performed well (AUC = 0.930), with the mean temperature of the warmest quarter, mean diurnal range, land cover type, and altitude being the most contributing variables. Consequent zoning based on the proportion of high-risk cells within each administrative unit suggested that five out of the 36 districts of the Republic are at high risk in the current climate conditions, with three more districts expected to demonstrate a high risk by 2060. This study presents the first-ever attempt at leptospirosis ecological modeling in Russia. Its results correspond well to the findings of other authors and underline the importance of considering ecological factors when conducting a leptospirosis risk assessment.