Delimitation of kala-azar risk areas in the district of Vaishali in Bihar (India) using a geo-environmental approach

Modelling spatiotemporal patterns of visceral leishmaniasis incidence in two endemic states in India using environment, bioclimatic and demographic data, 2013-2022

BACKGROUND

As of 2021, the National Kala-azar Elimination Programme (NKAEP) in India has achieved visceral leishmaniasis (VL) elimination (<1 case / 10,000 population/year per block) in 625 of the 633 endemic blocks (subdistricts) in four states. The programme needs to sustain this achievement and target interventions in the remaining blocks to achieve the WHO 2030 target of VL elimination as a public health problem. An effective tool to analyse programme data and predict/ forecast the spatial and temporal trends of VL incidence, elimination threshold, and risk of resurgence will be of use to the programme management at this juncture.

METHODOLOGY/PRINCIPAL FINDINGS

We employed spatiotemporal models incorporating environment, climatic and demographic factors as covariates to describe monthly VL cases for 8-years (2013-2020) in 491 and 27 endemic and non-endemic blocks of Bihar and Jharkhand states. We fitted 37 models of spatial, temporal, and spatiotemporal interaction random effects with covariates to monthly VL cases for 6-years (2013-2018, training data) using Bayesian inference via Integrated Nested Laplace Approximation (INLA) approach. The best-fitting model was selected based on deviance information criterion (DIC) and Watanabe-Akaike Information Criterion (WAIC) and was validated with monthly cases for 2019-2020 (test data). The model could describe observed spatial and temporal patterns of VL incidence in the two states having widely differing incidence trajectories, with >93% and 99% coverage probability (proportion of observations falling inside 95% Bayesian credible interval for the predicted number of VL cases per month) during the training and testing periods. PIT (probability integral transform) histograms confirmed consistency between prediction and observation for the test period. Forecasting for 2021-2023 showed that the annual VL incidence is likely to exceed elimination threshold in 16-18 blocks in 4 districts of Jharkhand and 33-38 blocks in 10 districts of Bihar. The risk of VL in non-endemic neighbouring blocks of both Bihar and Jharkhand are less than 0.5 during the training and test periods, and for 2021-2023, the probability that the risk greater than 1 is negligible (P<0.1). Fitted model showed that VL occurrence was positively associated with mean temperature, minimum temperature, enhanced vegetation index, precipitation, and isothermality, and negatively with maximum temperature, land surface temperature, soil moisture and population density.

CONCLUSIONS/SIGNIFICANCE

The spatiotemporal model incorporating environmental, bioclimatic, and demographic factors demonstrated that the KAMIS database of the national programmme can be used for block level predictions of long-term spatial and temporal trends in VL incidence and risk of outbreak / resurgence in endemic and non-endemic settings. The database integrated with the modelling framework and a dashboard facility can facilitate such analysis and predictions. This could aid the programme to monitor progress of VL elimination at least one-year ahead, assess risk of resurgence or outbreak in post-elimination settings, and implement timely and targeted interventions or preventive measures so that the NKAEP meet the target of achieving elimination by 2030.

Spatio-temporal modeling of visceral leishmaniasis in Midwest Brazil: An ecological study of 18-years data (2001-2018)

Visceral leishmaniasis (VL) is a neglected vector-borne disease associated with socioeconomic and environmental issues. In Brazil, epidemics of VL have occurred in major cities since 1980. Applied models for medical and epidemiological research have been used to assess the distribution and characteristics of disease endpoints and identify and characterize potential risk factors. This study described the demographic features of VL and modeled the spatio-temporal distribution of human VL cases and their relationship with underlying predicitve factors using generalized additive models. We conducted an ecological study covering an 18-year period from the first report of an autochthonous case of VL in Campo Grande, state of Mato Grosso do Sul, in 2001 to 2018. The urban area of the city has 74 neighborhoods, and they were the units of analysis of our work. Socioeconomic and demographic data available from Brazilian public databases were considered as covariables. A total of 1,855 VL cases were reported during the study period, with an annual mean incidence rate of 13.23 cases per 100,000 population and a cumulative crude incidence of 235.77 per 100,000 population. The results showed the rapid transition from epidemic to endemic and the centrifugal dispersal pattern of the disease. Moreover, the model highlighted that the urban quality of life index, which is calculated based on income, education, housing conditions, and environmental sanitation data, plays a role in VL occurrence. Our findings highlighted the potential for improving spatio-temporal segmentation of control measures and the cost-effectiveness of integrated disease management programs as soon as VL is difficult to control and prevent and has rapid geographical dispersion and increased incidence rates.

Environmental and socioeconomic risk factors associated with visceral and cutaneous leishmaniasis: a systematic review

We performed a systematic review of the literature published since 1900 about leishmaniasis a neglected vector-borne disease, focused on environmental and social risk factors for visceral (VL) and cutaneous leishmaniasis (CL) to better understand their impact on the incidence of disease. The search terms were "leishmaniasis" AND "risk factors" using Google Scholar, PudMed, and Scielo. We reviewed 177 articles, 95 studies for VL, 75 for CL, and 7 on both forms. We identified 14 categories of risk factors which were divided into three groups: socioeconomic (7), environmental (5), and climate (2) variables. Socioeconomic factors were also associated with disease incidence in vulnerable human populations of arid and tropical developing regions. Environmental and climate factors showed significant associations with the incidence of VL and CL in all the studies that considered them. Proximity to natural vegetation remnants increased disease risk in both the New and Old World while the climate conditions favorable for disease transmission differed among regions. We propose a common conceptual framework for both clinical forms that highlights networks of interaction among risk factors. In both clinical forms, the interplay of these factors played a major role in disease incidence. Although there are similarities in environmental and socioeconomic conditions that mediate the transmission cycle of tropical, arid, and Mediterranean regions, the behavior of vector and reservoirs in each region is different. Special attention should be given to the possibility of vector adaptation to urban environments in developing countries where populations with low socioeconomic status are particularly vulnerable to the disease.

Visceral Leishmaniasis in the Muzaffapur Demographic Surveillance Site: A Spatiotemporal Analysis

In the Indian subcontinent, visceral leishmaniasis (VL) has a strongly clustered distribution. The “index case approach” is promoted both for active case finding and indoor residual spraying (IRS). Uncertainty exists about the optimal radius. Buffer zones of 50–75 m around incident cases have been suggested for active case finding, for IRS the recommendation is to cover a radius of 500 m. Our aim was to establish optimal target areas both for IRS and for (re)active case finding. We plotted incident VL cases on a map per 6-month period (January–June or July–December) and drew buffers of 0 (same household), 50, 75, 100, 200, 300, 400, and 500 m around these cases. We then recorded total population and numbers of VL cases diagnosed over the next 6-month period in each of these buffers and beyond. We calculated incidence rate ratios (IRRs) using the population at more than 500 m from any case as reference category. There was a very strong degree of spatial clustering of VL with IRRs ranging from 45.2 (23.8–85.6) for those living in the same households to 14.6 (10.1–21.2) for those living within 75 m of a case diagnosed, during the previous period. Up to 500 m the IRR was still five times higher than that of the reference category. Our findings corroborate the rationale of screening not just household contacts but also those living within a perimeter of 50–75 m from an index case. For IRS, covering a perimeter of 500 m, appears to be a rational choice.

Decision tool for climate disasters and infectious disease at sub-national level in India: Ensuring a paradigm shift in health planning from prevalence to vulnerability

Climate change is considered as a distal determinant of public health which is increasing in importance. India, as an example, has a national action plan for climate change and human health. Sub-national (State) plans for climate change also exist, taking into account the health sector. The State of Bihar was selected for assessment because of its vulnerability (a function of exposure, sensitivity and adaptive capacity). A vulnerability framework was constructed by discussions with national and local-level specialists followed by weightage given by working in the field of climate and health with international exposure. A total of 15 districts were at a high risk of floods and these were considered for detailed analysis using the methodology for human development index as well as other examples in the field of environment. Climate health vulnerability index score were correlated with actual prevalence of flood mortality data of these 15 districts in year 2016. It was found that climate health vulnerability and flood mortality had negative low correlation of -0.25. In contrast for vector-borne diseases (VBD), both pre-flood and post-flood, the morbidity data had a correlation of 0.24 and 0.11 respectively. Possible reasons for a negative correlation for mortality could involve better preparedness by disaster district authorities. However, outbreak control is within the ambit of the health sector where a possible reason for decreased correlation coefficient in the post-flood period could be due to the impact on health facilities itself, thus leading to reduced reporting.

Trends in spatio-temporal dynamics of visceral leishmaniasis cases in a highly-endemic focus of Bihar, India: an investigation based on GIS tools

Background

Visceral leishmaniasis (VL) in Bihar State (India) continues to be endemic, despite the existence of effective treatment and a vector control program to control disease morbidity. A clear understanding of spatio-temporal distribution of VL may improve surveillance and control implementation. This study explored the trends in spatio-temporal dynamics of VL endemicity at a meso-scale level in Vaishali District, based on geographical information systems (GIS) tools and spatial statistical analysis.

Methods

A GIS database was used to integrate the VL case data from the study area between 2009 and 2014. All cases were spatially linked at a meso-scale level. Geospatial techniques, such as GIS-layer overlaying and mapping, were employed to visualize and detect the spatio-temporal patterns of a VL endemic outbreak across the district. The spatial statistic Moran’s I Index (Moran’s I) was used to simultaneously evaluate spatial-correlation between endemic villages and the spatial distribution patterns based on both the village location and the case incidence rate (CIR). Descriptive statistics such as mean, standard error, confidence intervals and percentages were used to summarize the VL case data.

Results

There were 624 endemic villages with 2719 (average 906 cases/year) VL cases during 2012–2014. The Moran’s I revealed a cluster pattern (P < 0.05) of CIR distribution at the meso-scale level. On average, 68 villages were newly-endemic each year. Of which 93.1% of villages’ endemicity were found to have occurred on the peripheries of the previous year endemic villages. The mean CIR of the endemic villages that were peripheral to the following year newly-endemic villages, compared to all endemic villages of the same year, was higher (P < 0.05).

Conclusion

The results show that the VL endemicity of new villages tends to occur on the periphery of villages endemic in the previous year. High-CIR plays a major role in the spatial dispersion of the VL cases between non-endemic and endemic villages. This information can help achieve VL elimination throughout the Indian subcontinent by improving vector control design and implementation in highly-endemic district.

Spatial Distribution of Phlebotomus argentipes (Diptera: Psychodidae) in Eastern India, a Case Study Evaluating Multispatial Resolution Remotely Sensed Environmental Evidence and Microclimatic Data

Remote sensing, a powerful tool for analyzing landscape factors, is being used to explore the spatial ecology of vectors of several diseases. This study aims to explore the role of buffer size in identification and quantification of geo-environmental factors from multispatial resolution satellite data and its application along with microclimatic data to kala-azar vector abundance modeling.Sand fly abundance and microclimatic data were collected from 210 sample sites during the premonsoon and postmonsoon season of 2014 from Muzaffarpur district of Bihar (India). Linear imaging self-scanning sensor (LISS-III; 23.5 m) and advanced wide field sensor (AWiFS; 56 m) imageries were used for generating environmental variables at 300- and 500-m buffer zones. Four analytical models of sand fly density were developed and evaluated for predictive accuracy.A total of 33 geo-environmental and four microclimatic variables were tested for the prediction of sand fly density, of which the best four were maximum temperature, relative humidity, Euclidean nearest-neighbor distance of settlement area to mixed bush-grass land, and surface water body. Predictive accuracy of the LISS-III models was found to be higher than AWiFS models at all buffer sizes.The results show that geo-environmental parameters and microclimatic data are the best predictors for sand fly density modeling. Buffer sizes play an important role in identifying the explanatory variables. Model parameters may be useful in identifying predisposing factors of sand fly habitat suitability at the micro level.

Socioeconomic Inequalities in Neglected Tropical Diseases: A Systematic Review

BACKGROUND

Neglected tropical diseases (NTDs) are generally assumed to be concentrated in poor populations, but evidence on this remains scattered. We describe within-country socioeconomic inequalities in nine NTDs listed in the London Declaration for intensified control and/or elimination: lymphatic filariasis (LF), onchocerciasis, schistosomiasis, soil-transmitted helminthiasis (STH), trachoma, Chagas' disease, human African trypanosomiasis (HAT), leprosy, and visceral leishmaniasis (VL).

METHODOLOGY

We conducted a systematic literature review, including publications between 2004-2013 found in Embase, Medline (OvidSP), Cochrane Central, Web of Science, Popline, Lilacs, and Scielo. We included publications in international peer-reviewed journals on studies concerning the top 20 countries in terms of the burden of the NTD under study.

PRINCIPAL FINDINGS

We identified 5,516 publications, of which 93 met the inclusion criteria. Of these, 59 papers reported substantial and statistically significant socioeconomic inequalities in NTD distribution, with higher odds of infection or disease among poor and less-educated people compared with better-off groups. The findings were mixed in 23 studies, and 11 studies showed no substantial or statistically significant inequality. Most information was available for STH, VL, schistosomiasis, and, to a lesser extent, for trachoma. For the other NTDs, evidence on their socioeconomic distribution was scarce. The magnitude of inequality varied, but often, the odds of infection or disease were twice as high among socioeconomically disadvantaged groups compared with better-off strata. Inequalities often took the form of a gradient, with higher odds of infection or disease each step down the socioeconomic hierarchy. Notwithstanding these inequalities, the prevalence of some NTDs was sometimes also high among better-off groups in some highly endemic areas.

CONCLUSIONS

While recent evidence on socioeconomic inequalities is scarce for most individual NTDs, for some, there is considerable evidence of substantially higher odds of infection or disease among socioeconomically disadvantaged groups. NTD control activities as proposed in the London Declaration, when set up in a way that they reach the most in need, will benefit the poorest populations in poor countries.

Understanding the transmission dynamics of Leishmania donovani to provide robust evidence for interventions to eliminate visceral leishmaniasis in Bihar, India

Visceral Leishmaniasis (VL) is a neglected vector-borne disease. In India, it is transmitted to humans by Leishmania donovani-infected Phlebotomus argentipes sand flies. In 2005, VL was targeted for elimination by the governments of India, Nepal and Bangladesh by 2015. The elimination strategy consists of rapid case detection, treatment of VL cases and vector control using indoor residual spraying (IRS). However, to achieve sustained elimination of VL, an appropriate post elimination surveillance programme should be designed, and crucial knowledge gaps in vector bionomics, human infection and transmission need to be addressed. This review examines the outstanding knowledge gaps, specifically in the context of Bihar State, India.The knowledge gaps in vector bionomics that will be of immediate benefit to current control operations include better estimates of human biting rates and natural infection rates of P. argentipes, with L. donovani, and how these vary spatially, temporally and in response to IRS. The relative importance of indoor and outdoor transmission, and how P. argentipes disperse, are also unknown. With respect to human transmission it is important to use a range of diagnostic tools to distinguish individuals in endemic communities into those who: 1) are to going to progress to clinical VL, 2) are immune/refractory to infection and 3) have had past exposure to sand flies.It is crucial to keep in mind that close to elimination, and post-elimination, VL cases will become infrequent, so it is vital to define what the surveillance programme should target and how it should be designed to prevent resurgence. Therefore, a better understanding of the transmission dynamics of VL, in particular of how rates of infection in humans and sand flies vary as functions of each other, is required to guide VL elimination efforts and ensure sustained elimination in the Indian subcontinent. By collecting contemporary entomological and human data in the same geographical locations, more precise epidemiological models can be produced. The suite of data collected can also be used to inform the national programme if supplementary vector control tools, in addition to IRS, are required to address the issues of people sleeping outside.

Validation of a Previously Developed Geospatial Model That Predicts the Prevalence of Listeria monocytogenes in New York State Produce Fields

Technological advancements, particularly in the field of geographic information systems (GIS), have made it possible to predict the likelihood of foodborne pathogen contamination in produce production environments using geospatial models. Yet, few studies have examined the validity and robustness of such models. This study was performed to test and refine the rules associated with a previously developed geospatial model that predicts the prevalence of Listeria monocytogenes in produce farms in New York State (NYS). Produce fields for each of four enrolled produce farms were categorized into areas of high or low predicted L. monocytogenes prevalence using rules based on a field's available water storage (AWS) and its proximity to water, impervious cover, and pastures. Drag swabs (n = 1,056) were collected from plots assigned to each risk category. Logistic regression, which tested the ability of each rule to accurately predict the prevalence of L. monocytogenes, validated the rules based on water and pasture. Samples collected near water (odds ratio [OR], 3.0) and pasture (OR, 2.9) showed a significantly increased likelihood of L. monocytogenes isolation compared to that for samples collected far from water and pasture. Generalized linear mixed models identified additional land cover factors associated with an increased likelihood of L. monocytogenes isolation, such as proximity to wetlands. These findings validated a subset of previously developed rules that predict L. monocytogenes prevalence in produce production environments. This suggests that GIS and geospatial models can be used to accurately predict L. monocytogenes prevalence on farms and can be used prospectively to minimize the risk of preharvest contamination of produce.

Visceral leishmaniasis diagnosis and reporting delays as an obstacle to timely response actions in Nepal and India

Background

To eliminate visceral leishmaniasis (VL) in India and Nepal, challenges of VL diagnosis, treatment and reporting need to be identified. Recent data indicate that VL is underreported and patients face delays when seeking treatment. Moreover, VL surveillance data might not reach health authorities on time. This study quantifies delays for VL diagnosis and treatment, and analyses the duration of VL reporting from district to central health authorities in India and Nepal.

Methods

A cross-sectional study conducted in 12 districts of Terai region, Nepal, and 9 districts of Bihar State, India, in 2012. Patients were interviewed in hospitals or at home using a structured questionnaire, health managers were interviewed at their work place using a semi-structured questionnaire and in-depth interviews were conducted with central level health managers. Reporting formats were evaluated. Data was analyzed using two-tailed Mann-Whitney U or Fisher’s exact test.

Results

92 VL patients having experienced 103 VL episodes and 49 district health managers were interviewed. Patients waited in Nepal 30 days (CI 18-42) before seeking health care, 3.75 times longer than in Bihar (8d; CI 4-12). Conversely, the lag time from seeking health care to receiving a VL diagnosis was 3.6x longer in Bihar (90d; CI 68-113) compared to Nepal (25d; CI 13-38). The time span between diagnosis and treatment was short in both countries. VL reporting time was in Nepal 19 days for sentinel sites and 76 days for “District Public Health Offices (DPHOs)”. In Bihar it was 28 days for “District Malaria Offices”. In Nepal, 73% of health managers entered data into computers compared to 16% in Bihar. In both countries reporting was mainly paper based and standardized formats were rarely used.

Conclusions

To decrease the delay between onset of symptoms and getting a proper diagnosis and treatment the approaches in the two countries vary: In Nepal health education for seeking early treatment are needed while in Bihar the use of private and non-formal practitioners has to be discouraged. Reinforcement of VL sentinel reporting in Bihar, reorganization of DPHOs in Nepal, introduction of standardized reporting formats and electronic reporting should be conducted in both countries.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-015-0767-5) contains supplementary material, which is available to authorized users.

Appraisal of Phlebotomus argentipes habitat suitability using a remotely sensed index in the kala-azar endemic focus of Bihar, India

Visceral leishmaniasis, or kala-azar, is recognised as a serious emerging public health problem in India. In this study, environmental parameters, such as land surface temperature (LST) and renormalised difference vegetation indices (RDVI), were used to delineate the association between environmental variables and Phlebotomus argentipes abundance in a representative endemic region of Bihar, India. The adult P. argentipes were collected between September 2009-February 2010 using the hand-held aspirator technique. The distribution of P. argentipes was analysed with the LST and RDVI of the peak and lean seasons. The association between environmental covariates and P. argentipes density was analysed a multivariate linear regression model. The sandfly density at its maximum in September, whereas the minimum density was recorded in January. The regression model indicated that the season, minimum LST, mean LST and mean RDVI were the best environmental covariates for the P. argentipes distribution. The final model indicated that nearly 74% of the variance of sandfly density could be explained by these environmental covariates. This approach might be useful for mapping and predicting the distribution of P. argentipes, which may help the health agencies that are involved in the kala-azar control programme focus on high-risk areas.