Bayesian geostatistical modeling of leishmaniasis incidence in Brazil

Bayesian spatio-temporal modeling to assess the effect of land-use changes on the incidence of Cutaneous Leishmaniasis in the Brazilian Amazon

Cutaneous Leishmaniasis (CL) is a vector-borne disease caused by a protozoan of the genus Leishmania and is considered one of the most important neglected tropical diseases. The Brazilian Amazon Forest harbors one of the highest diversity of Leishmania parasites and vectors and is one of the main focuses of the disease in the Americas. Previous studies showed that some types of anthropogenic disturbances have affected the abundance and distribution of CL vectors and hosts; however, few studies have thoroughly investigated the influence of different classes of land cover and land-use changes on the disease transmission risk. Here, we quantify the effect of land use and land-cover changes on the incidence of CL in all municipalities within the Brazilian Amazon Forest, from 2001 to 2017. We used a structured spatiotemporal Bayesian model to assess the effect of forest cover, agriculture, livestock, extractivism, and- deforestation on CL incidence, accounting for confounding variables such as population, climate, socioeconomic, and spatiotemporal random effects. We found that the increased risk of CL was associated with deforestation, especially modulated by a positive interaction between forest cover and livestock. Landscapes with ongoing deforestation for extensive cattle ranching are typically found in municipalities within the Amazon Frontier, where a high relative risk for CL was also identified. These findings provide valuable insights into developing effective public health policies and land-use planning to ensure healthier landscapes for people.

Tegumentary leishmaniasis in Brazil: priority municipalities and spatiotemporal relative risks from 2001 to 2020

Understanding the distribution of tegumentary leishmaniasis (TL) in different periods enables the adequate conduction of actions at the public health level. The present study analyzes the spatiotemporal evolution of TL incidence rates in the municipalities of Brazil and identifies priority areas from 2001 to 2020. Notifications of new cases were analyzed employing space-time scan statistics and Local Indicators of Spatial Association. As TL incidence rates presented a downward trend in most Brazilian municipalities, spatiotemporal clusters of high relative risks (RR) were more frequent in the first decade of the series. There was a concentration of those clusters in the North and Northeast regions, mainly in the Legal Amazon area. More recent high-RR areas were identified in municipalities of different regions. The number of priority municipalities showed a stable trend in Brazil. There was a great concentration of such municipalities in the states of Acre, Mato Grosso, Rondônia, Pará, and Amapá, as well as large areas in Roraima, Amazonas, Maranhão, and Tocantins, and smaller areas in the states of Goiás, Ceará, Bahia, Minas Gerais, São Paulo, and Paraná. The present study contributes to the understanding of the historical evolution of TL in Brazil and subsidizes actions to combat the disease.

Causal association between environmental variables and the excess cases of cutaneous leishmaniasis in Colombia: are we looking to the wrong side?

Our main aim was to estimate and compare the effects of six environmental variables (air temperature, soil temperature, rainfall, runoff, soil moisture, and the enhanced vegetation index) on excess cases of cutaneous leishmaniasis in Colombia. We used epidemiological data from the Colombian Public Health Surveillance System (January 2007 to December 2019). Environmental data were obtained from remote sensing sources including the National Oceanic and Atmospheric Administration, the Global Land Data Assimilation System (GLDAS), and the Moderate Resolution Imaging Spectroradiometer. Data on population were obtained from the TerriData dataset. We implemented a causal inference approach using a machine learning algorithm to estimate the causal association of the environmental variables on the monthly occurrence of excess cases of cutaneous leishmaniasis. The results showed that the largest causal association corresponded to soil moisture with a lag of 3 months, with an average increase of 8.0% (95% confidence interval [CI] 7.7-8.3%) in the occurrence of excess cases. The temperature-related variables (air temperature and soil temperature) had a positive causal effect on the excess cases of cutaneous leishmaniasis. It is noteworthy that rainfall did not have a statistically significant causal effect. This information could potentially help to monitor and control cutaneous leishmaniasis in Colombia, providing estimates of causal effects using remote sensor variables.

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 analysis of the visceral leishmaniasis in the state of Alagoas, Brazil

Abstract Visceral leishmaniosis is a neglected tropical disease. We evaluated the spatial distribution of cases of visceral leishmaniosis in the state of Alagoas, Brazil. All cases of VL, registered by the health department, were analyzed and georeferenced. Results: Between 2008 and 2017, 97.1% of the municipalities presented sporadic classification of transmission. With temporal evolution, the incidence of cases of visceral leishmaniosis was concentrated in most municipalities in the microregion of Santana do Ipanema-AL. Space-time analysis, if considered, may promote the improvement of surveillance and control actions of visceral leishmaniosis.

Spatio-temporal distribution and contributing factors of tegumentary and visceral leishmaniasis: A comparative study in Bahia, Brazil

Tegumentary (TL) and visceral (VL) leishmaniasis are neglected zoonotic diseases in Brazil, caused by different parasites and transmitted by various vector species. This study investigated and compared spatio-temporal patterns of TL and VL from 2007 to 2020 in the state of Bahia, Brazil, and their correlations with extrinsic factors. The results showed that the total number of cases of both TL and VL were decreasing. The number of municipalities with reported cases reduced for TL over time but remained almost unchanged for VL. There were few municipalities with reported both diseases. Statistical analysis showed that local TL incidence was associated positively with natural forest. Local VL incidence was associated positively with Cerrado (Brazilian savannah) vegetation. This study identified different patterns of occurrence of VL and TL and the risk areas that could be prioritized for epidemiological surveillance.

Association between the potential distribution of Lutzomyia longipalpis and Nyssomyia whitmani and leishmaniasis incidence in Piauí State, Brazil

BACKGROUND

Leishmaniases are vector borne diseases caused by Leishmania spp. parasites transmitted by female sandflies (Diptera: Psychodidae) whose geographic distribution is influenced by environmental factors. Among the main tools for studying the distribution of vector species, modeling techniques are used to analyze the influence of climatic and environmental factors on the distribution of these insects and their association with human cases of the disease.

METHODOLOGY/PRINCIPAL FINDINGS

Here, we used a multiscale ecological niche modeling approach to assess the environmental suitability of sandfly vectors of the etiological agents of Visceral (VL) and American Cutaneous Leishmaniasis (ACL) in Piauí state, northeastern Brazil, and then evaluated their relationship with human disease incidence. For this, we obtained the geographic coordinates of the vector species Lutzomyia longipalpis and Nyssomyia whitmani through literature review, online databases and unpublished records. These data were used for the development of predictive models of the distribution of both sandflies species based on climatic and environmental variables. Finally, the environmental suitability for the presence of these vectors was compared with the incidence of both the diseases at the municipality level. The final models for each sandfly species showed good predictive powers with performance metric values of 0.889 for Lu. longipalpis and 0.776 for Ny. whitmani. The areas with greater environmental suitability for the presence of these species were concentrated in the central-north region of Piauí and coincide with the location of those municipalities presenting higher incidences of VL and ACL, situated in the central-north and extreme north of the state, respectively. The south and southeast regions of Piauí state have low incidence of these diseases and presented low environmental suitability for the presence of both vectors.

CONCLUSIONS/SIGNIFICANCE

We discuss how predictive modeling can guide entomological and epidemiological surveillances and recommend an increased supervision and control activities in Teresina (capital of the state of Piaui), Altos and Pedro II, in addition to other municipalities with similar social and environmental characteristics.

Distribution and Risk of Cutaneous Leishmaniasis in Khyber Pakhtunkhwa, Pakistan

Cutaneous leishmaniasis (CL) is a zoonotic infection caused by obligate intracellular protozoa of the genus Leishmania. This study aimed to investigate CL in Khyber Pakhtunkhwa, Pakistan and to estimate the risk of epidemics. Clinico-epidemiological data of 3188 CL patients were collected from health facilities in 2021. Risk factors were analyzed using the chi-square test. ArcGIS V.10.7.1 was applied for spatial analysis. The association between CL occurrence and climatic variables was examined by Bayesian geostatistical analysis. The clinical data revealed males or individuals younger than 20 years old were more affected. Most patients presented with a single lesion, and the face was the most attacked body part. CL was prevalent in the southern region in winter. A proportional symbol map, a choropleth map, and a digital elevation model map were built to show the distribution of CL. Focal transmission was predicted by inverse distance weighting interpolation. Cluster and outlier analysis identified clusters in Bannu, Dir Lower, and Mardan, and hotspot analysis suggested Bannu as a high-risk foci. Bayesian geostatistical analysis indicated that increasing precipitation and temperature as well as low altitudes were associated with CL infection. The study has provided important information for public health sectors to develop intervention strategies for future CL epidemics.

Time series analysis of leishmaniasis incidence in Sri Lanka: evidence for humidity-associated fluctuations

Leishmaniasis is a vector-borne disease of which the transmission is highly influenced by climatic factors, whereas the nature and magnitude differ between geographical regions. The effects of climatic variables on leishmaniasis in Sri Lanka are poorly investigated. The present study focused on time-series analysis of leishmaniasis cases reported from Sri Lanka with selected climatic variables. Variance stabilized time series of leishmaniasis patients of entire Sri Lanka and major districts from 2014 to 2018 was fitted to autoregressive integrated moving average (ARIMA) models. All the possible models were generated by assigning different values for autoregression and moving average terms using a function written in R statistical program. The top ten models with the lowest Akaike information criterion (AIC) values were selected by writing another function. These models were further evaluated using RMSE and MAPE error parameters to select the optimal model for each area. Cross-autocorrelation analyses were performed to assess the associations between climate and the leishmaniasis incidence. Most associated lags of each variable were integrated into the optimal models to determine the true effects imposed. The optimal models varied depending on the area. SARIMA (0,1,1) (1,0,0)₁₂ was optimal for the country level. All the forecasts were within the 95% confidence intervals. Humidity was the most notable factor associated with leishmaniasis, which could be attributed to the positive impacts on sand fly activity. Rainfall showed a negative impact probably as a result of flooding of sand fly larval habitats. The ARIMA-based models performed well for the prediction of leishmaniasis in the short term.

Spatio-Temporal Pattern and Meteo-Climatic Determinants of Visceral Leishmaniasis in Italy

Historically, visceral leishmaniasis (VL) in Italy was constrained to Mediterranean areas. However, in the last 20 years, sand fly vectors and human cases of VL have been detected in northern Italy, traditionally classified as a cold area unsuitable for sand fly survival. We aim to study the spatio-temporal pattern and climatic determinants of VL incidence in Italy. National Hospital Discharge Register records were used to identify incident cases of VL between 2009 and 2016. Incident rates were computed for each year (N = 8) and for each province (N = 110). Data on mean temperature and cumulative precipitation were obtained from the ERA5-Land re-analysis. Age- and sex-standardized incidence rates were modeled with Bayesian spatial and spatio-temporal conditional autoregressive Poisson models in relation to the meteo-climatic parameters. Statistical inference was based on Monte Carlo−Markov chains. We identified 1123 VL cases (incidence rate: 2.4 cases/1,000,000 person-years). The highest incidence rates were observed in southern Italy, even though some areas of northern Italy experienced high incidence rates. Overall, in the spatial analysis, VL incidence rates were positively associated with average air temperatures (β for 1 °C increase in average mean average temperature: 0.14; 95% credible intervals (CrI): 0.01, 0.27) and inversely associated with average precipitation (β for 20 mm increase in average summer cumulative precipitation: −0.28, 95% CrI: −0.42, −0.13). In the spatio-temporal analysis, no association between VL cases and season-year specific temperature and precipitation anomalies was detected. Our findings indicate that VL is endemic in the whole Italian peninsula and that climatic factors, such as air temperature and precipitation, might play a relevant role in shaping the geographical distribution of VL cases. These results support that climate change might affect leishmaniasis distribution in the future.

Environmental, Climatic, and Parasite Molecular Factors Impacting the Incidence of Cutaneous Leishmaniasis Due to Leishmania tropica in Three Moroccan Foci

Cutaneous leishmaniasis (CL) occurring due to Leishmania tropica is a public health problem in Morocco. The distribution and incidence of this form of leishmaniasis have increased in an unusual way in the last decade, and the control measures put in place are struggling to slow down the epidemic. This study was designed to assess the impact of climatic and environmental factors on CL in L. tropica foci. The data collected included CL incidence and climatic and environmental factors across three Moroccan foci (Foum Jemaa, Imintanout, and Ouazzane) from 2000 to 2019. Statistical analyses were performed using the linear regression model. An association was found between the occurrence of CL in Imintanout and temperature and humidity (r² = 0.6076, df = (1.18), p-value = 3.09 × 10⁻⁵; r² = 0.6306, df = (1.18), p-value = 1.77 × 10⁻⁵). As a second objective of our study, we investigated the population structure of L.tropica in these three foci, using the nuclear marker internal transcribed spacer 1 (ITS1). Our results showed a low-to-medium level of geographic differentiation among the L.tropica populations using pairwise differentiation. Molecular diversity indices showed a high genetic diversity in Foum Jemaa and Imintanout; indeed, 29 polymorphic sites were identified, leading to the definition of 13 haplotypes. Tajima’s D and Fu’s F test statistics in all populations were not statistically significant, and consistent with a population at drift–mutation equilibrium. Further analysis, including additional DNA markers and a larger sample size, could provide a more complete perspective of L. tropica’s population structure in these three regions. In addition, further research is needed to better understand the impact of climatic conditions on the transmission cycle of Leishmania, allowing both for the development of effective control measures, and for the development of a predictive model for this parasitosis.

Bayesian Geostatistical Modeling to Assess Malaria Seasonality and Monthly Incidence Risk in Eswatini

Eswatini is on the brink of malaria elimination and had however, had to shift its target year to eliminate malaria on several occasions since 2015 as the country struggled to achieve its zero malaria goal. We conducted a Bayesian geostatistical modeling study using malaria case data. A Bayesian distributed lags model (DLM) was implemented to assess the effects of seasonality on cases. A second Bayesian model based on polynomial distributed lags was implemented on the dataset to improve understanding of the lag effect of environmental factors on cases. Results showed that malaria increased during the dry season with proportion 0.051 compared to the rainy season with proportion 0.047 while rainfall of the preceding month (Lag2) had negative effect on malaria as it decreased by proportion − 0.25 (BCI: − 0.46, − 0.05). Night temperatures of the preceding first and second month were significantly associated with increased malaria in the following proportions: at Lag1 0.53 (BCI: 0.23, 0.84) and at Lag2 0.26 (BCI: 0.01, 0.51). Seasonality was an important predictor of malaria with proportion 0.72 (BCI: 0.40, 0.98). High malaria rates were identified for the months of July to October, moderate rates in the months of November to February and low rates in the months of March to June. The maps produced support-targeted malaria control interventions. The Bayesian geostatistical models could be extended for short-term and long-term forecasting of malaria supporting-targeted response both in space and time for effective elimination.

Geospatial modeling of pre-intervention nodule prevalence of Onchocerca volvulus in Ethiopia as an aid to onchocerciasis elimination

Background

Onchocerciasis is a neglected tropical filarial disease transmitted by the bites of blackflies, causing blindness and severe skin lesions. The change in focus for onchocerciasis management from control to elimination requires thorough mapping of pre-control endemicity to identify areas requiring interventions and to monitor progress. Onchocerca volvulus nodule prevalence in sub-Saharan Africa is spatially continuous and heterogeneous, and highly endemic areas may contribute to transmission in areas of low endemicity or vice-versa. Ethiopia is one such onchocerciasis-endemic country with heterogeneous O. volvulus nodule prevalence, and many districts are still unmapped despite their potential for onchocerciasis transmission.

Methodology/Principle findings

A Bayesian geostatistical model was fitted for retrospective pre-intervention nodule prevalence data collected from 916 unique sites and 35,077 people across Ethiopia. We used multiple environmental, socio-demographic, and climate variables to estimate the pre-intervention prevalence of O. volvulus nodules across Ethiopia and to explore their relationship with prevalence. Prevalence was high in southern and northwestern Ethiopia and low in Ethiopia’s central and eastern parts. Distance to the nearest river (RR: 0.9850, 95% BCI: 0.9751–0.995), precipitation seasonality (RR: 0.9837, 95% BCI: 0.9681–0.9995), and flow accumulation (RR: 0.9586, 95% BCI: 0.9321–0.9816) were negatively associated with O. volvulus nodule prevalence, while soil moisture (RR: 1.0218, 95% BCI: 1.0135–1.0302) was positively associated. The model estimated the number of pre-intervention cases of O. volvulus nodules in Ethiopia to be around 6.48 million (95% BCI: 3.53–13.04 million).

Conclusions/Significance

Nodule prevalence distribution was correlated with habitat suitability for vector breeding and associated biting behavior. The modeled pre-intervention prevalence can be used as a guide for determining priorities for elimination mapping in regions of Ethiopia that are currently unmapped, most of which have comparatively low infection prevalence.

Areas with unknown onchocerciasis endemicity may pose a threat to eliminating transmission because they may re-introduce onchocerciasis to areas where interventions have been successful. Additionally, because vectors (and thus Onchocerca volvulus transmission) have specific ecological requirements for growth and development, changes in these ecological factors due to human activities (deforestation, modification of river flows by dam construction, climate change) might change patterns of parasite transmission and endemicity. To estimate the impact of environmental changes, we must first identify ecological factors determining prevalence. We have employed Bayesian geostatistical modeling to create a nationwide O. volvulus nodule prevalence map for Ethiopia based on pre-intervention nodule prevalence data and have explored the effect of environmental variables on nodule prevalence. We estimated the number of pre-intervention cases of nodules and associated uncertainty in previously unmapped areas of Ethiopia to identify areas that need additional data to increase the prediction accuracy. Hydrological variables such as distance to the nearest river, precipitation seasonality, soil moisture, and flow accumulation are associated significantly with O. volvulus nodule prevalence. We show that the spatial distribution of nodule prevalence can be estimated based on ecological data and that predicted prevalence can be used as a guide to prioritize pre-intervention mapping.

Predictive modeling of sand fly distribution incriminated in the transmission of Leishmania (Viannia) braziliensis and the incidence of Cutaneous Leishmaniasis in the state of Paraná, Brazil

Southern Brazil concentrates a considerable number of cases of cutaneous leishmaniasis reported since 1980, and Paraná is the state that most records CL cases in the region. The main sand fly species incriminated as vectors of Leishmania (Viannia) braziliensis (Vianna,1911) are Migonemyia (Migonemyia) migonei (França, 1920), Nyssomyia (Nyssomyia) neivai (Pinto, 1926) and Nyssomyia (Nyssomyia) whitmani (Antunes & Coutinho, 1936). In this study, we evaluated areas with climatic suitability for the distribution of these vectors and correlated these data with CL incidence in the state. The occurrence points of Mg. migonei, Ny. neivai, and Ny. whitmani were extracted from a literature review and field data. For CL analysis in the state of Paraná, data were obtained from the Informatics Department of the Unified Health System of Brazil (DATASUS), covering the period from 2001 to 2019. The layers of bioclimatic variables from the WorldClim database were used in the study. Species distribution modeling was developed using the MaxEnt Software version 3.4.4. ArcGIS software version 10.5 was used to develop suitability maps and the graphical representation of disease incidence. The AUC values were acceptable for all models (> 0,8). Bioclimatic variables BIO13 and BIO14 were the most influential in the distribution of Mg. migonei, while BIO19 and BIO6 were the variables that most influenced the distribution of Ny. neivai, and Ny. whitmani was most influenced by variables BIO5 and BIO9. During 19 years, 4992 cases of CL were reported in the state by 286 municipalities (71,6%). Northern Paraná showed the highest number of areas with very high and high climatic suitability for the occurrence of these species, coinciding with the highest number of CL cases. The modeling tools allowed analyzing the association between climatic variables and the geographical distribution of CL in the state. Moreover, they provided a better understanding of the climatic conditions related to the distribution of different species, favoring the monitoring of risk areas, the implementation of preventive measures, risk awareness, early and accurate diagnosis, and consequent timely treatment.

Gingival inflammation and hematological parameters in children with visceral leishmaniasis: A cross-sectional study

AIMS

This cross-sectional study aimed to assess gingival inflammation in 67 children aged 1-8 years (mean age 3.07) with visceral leishmaniasis (VL) at the time of hospitalization (D1) and 7 days after the first interview (D7) and compare the main hematological changes between the two time points.

METHODS AND RESULTS

The biofilm index was verified at D1 and D7 using the Simplified Oral Hygiene Index (OHI-S) and the gingival inflammation index based on the gingival index (GI), along with hematological parameters. The mean OHI-S was 2.35 ± 0.93 at D1 and 1.47 ± 0.75 at D7. The mean GI was 0.56 ± 0.59 at D1 and 0.11 ± 0.32 at D7. The variable OHI-S at D1 could predict GI at D1, as an increase in the OHI-S value by one unit was associated with an increase in the GI D1 value by 0.36 units (p < .05). Multivariate linear regression analysis showed that none of the hematological variables were predictive of gingival inflammation at D1 and D7 (p > .05).

CONCLUSION

Children with VL had poor oral hygiene on the first day of hospitalization. Clinically, the oral hygiene status progressed from poor at D1 to regular at D7. After 7 days the gingival bleeding scores also reduces.

Natural compounds based chemotherapeutic against Chagas disease and leishmaniasis: mitochondrion as a strategic target

Over the past years, natural products have been explored in order to find biological active substances to treat various diseases. Regarding their potential action against parasites such as trypanosomatids, specially Trypanosoma cruzi and Leishmania spp., much advance has been achieved. Extracts and purified molecules of several species from genera Piper, Tanacetum, Porophyllum, and Copaifera have been widely investigated by our research group and exhibited interesting antitrypanosomal and antileishmanial activities. These natural compounds affected different structures in parasites, and we believe that the mitochondrion is a strategic target to induce parasite death. Considering that these trypanosomatids have a unique mitochondrion, this cellular target has been extensively studied aiming to find more selective drugs, since the current treatment of these neglected tropical diseases has some challenges such as high toxicity and prolonged treatment time. Here, we summarise some results obtained with natural products from our research group and we further highlighted some strategies that must be considered to finally develop an effective chemotherapeutic agent against these parasites.

Environmental and socioeconomic risk factors for visceral and cutaneous leishmaniasis in São Paulo, Brazil

Leishmaniasis is a vector-borne disease caused by the protozoan Leishmania spp. mainly affecting individuals of low socioeconomic status. In tropical regions the transmission risk to humans depends not only on environmental factors, such as vegetation cover and climate, but also on the socioeconomic characteristics of human populations. However, the relative contribution of these factors to disease risk and incidence is not well understood. Yet this information is critical for the development of epidemiological surveillance schemes and control practices. Leishmaniasis cases have increased in São Paulo state, Brazil over recent years but the underlying risk factors for transmission remain understudied. Here, we use generalized linear mixed models to quantify the association between occurrence and incidence (number of cases) of cutaneous (CL) and visceral (VL) leishmaniasis from 1998 to 2015, and landscape (native vegetation cover), climate (seasonal and interannual variation in precipitation and temperature) and socioeconomic factors (population, number of cattle heads, Human Development Index - HDI, Gini inequality index and income per capita) across the 645 municipalities of São Paulo state, Brazil. For CL, probability of occurrence was greater in municipalities with high native vegetation cover and economic inequality and in years with greater average winter precipitation. For VL, probability of occurrence was greater in years with high minimum spring precipitation and maximum annual temperatures, and in municipalities with larger HDI values and a greater number of cattle heads. The number of VL cases increased during years with high mean fall precipitation and, for both CL and VL the number of cases was greater in years of high annual mean temperature. Understanding how these risk factors influence spatial and temporal variation in the risk and incidence of leishmaniasis can contribute to the development of effective public health policies and interventions.

Opisthorchis viverrini and Strongyloides stercoralis mono- and co-infections: Bayesian geostatistical analysis in an endemic area, Thailand

Parasitic infections caused by Opisthorchis viverrini and Strongyloides stercoralis remain a major public health threat in the Greater Mekong Sub-region. An understanding of climate and other environmental influences on the geographical distribution and emergence of parasitic diseases is a crucial step to guide targeted control and prevention programs. A parasitological survey was conducted from 2008 to 2013 and included 12,554 individuals (age between 20 and 60 years) from 142 villages in five districts in Khon Kaen Province, Thailand. Geographical information systems, remote sensing technologies and a Bayesian geostatistical framework were used to develop models for O. viverrini and S. stercoralis mono- and co-infections in areas where both parasites are known to co-occur. The results indicate that male sex, increased age, altitude, precipitation, and land surface temperature have influenced the infection rate and geographical distribution of mono- and co-infections of O. viverrini and S. stercoralis in this area. Males were 6.69 times (95% CrI: 5.26-8.58) more likely to have O. viverrini - S. stercoralis co-infection. We observed that O. viverrini and S. stercoralis mono-infections display distinct spatial pattern, while co-infection is predicted in the center and southeast of the study area. The observed spatial clustering of O. viverrini and S. stercoralis provides valuable information for the spatial targeting of prevention interventions in this area.

Spatial-temporal pattern of cutaneous leishmaniasis in Brazil

Background

Cutaneous leishmaniasis (CL) is a vector-borne disease classified by the World Health Organization as one of the most neglected tropical diseases. Brazil has the highest incidence of CL in America and is one of the ten countries in the world with the highest number of cases. Understanding the spatiotemporal dynamics of CL is essential to provide guidelines for public health policies in Brazil. In the present study we used a spatial and temporal statistical approach to evaluate the dynamics of CL in Brazil.

Methods

We used data of cutaneous leishmaniasis cases provided by the Ministry of Health of Brazil from 2001 to 2017. We calculated incidence rates and used the Mann–Kendall trend test to evaluate the temporal trend of CL in each municipality. In addition, we used Kuldorff scan method to identify spatiotemporal clusters and emerging hotspots test to evaluate hotspot areas and their temporal trends.

Results

We found a general decrease in the number of CL cases in Brazil (from 15.3 to 8.4 cases per 100 000 habitants), although 3.2% of municipalities still have an increasing tendency of CL incidence and 72.5% showed no tendency at all. The scan analysis identified a primary cluster in northern and central regions and 21 secondary clusters located mainly in south and southeast regions. The emerging hotspots analysis detected a high spatial and temporal variability of hotspots inside the main cluster area, diminishing hotspots in eastern Amazon and permanent, emerging, and new hotspots in the states of Amapá and parts of Pará, Roraima, Acre and Mato Grosso. The central coast the state of Bahia is one of the most critical areas due to the detection of a cluster of the highest rank in a secondary cluster, and because it is the only area identified as an intensifying hotspot.

Conclusions

Using a combination of statistical methods we were able to detect areas of higher incidence of CL and understand how it changed over time. We suggest that these areas, especially those identified as permanent, new, emerging and intensifying hotspots, should be targeted for future research, surveillance, and implementation of vector control measures.

Graphic abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s40249-021-00872-x.

Spatiotemporal patterns of cutaneous leishmaniasis in the district upper and lower Dir, Khyber Pakhtunkhwa, Pakistan: A GIS-based spatial approaches

While Cutaneous leishmaniasis (CL) is not a life-threatening disease, it leads to devastating effects on local community. CL is widely scattered manifesting a noticeable epidemiological pattern around the globe. The present study was planned to address the role of Geographic Information System (GIS) using CL clinico-epidemiological data to determine the high-risk areas of CL. Recorded data (2014-2018) of 3630 positive individuals was collected from Basic Health Units of the Upper and Lower Dir Districts, Khyber Pakhtunkhwa, Pakistan. Descriptive and statistical analysis was used for clinico-epidemiological characterization. For spatial analysis, ArcGIS V.10.3 was used and the CL average incidence was tagged on the proportional, choropleth, and digital elevation model maps. For focal transmission and high-risk zones, Inverse Density Weight (IDW) spatial interpolation, focal statistics, hot spot, cluster and outlier, and Bayesian geostatistical analysis were used. The trend of CL cases was elevated from 2014 to 2016 except for 2017 and 2018. Individuals of both genders younger than 20 years old were highly susceptible. Single lesions were more prominent (56%) and frequently affected facial parts (51%). The size and pretreatment duration of the CL lesion was significantly associated. Spatially, a choropleth map displayed the maximum CL incidences in Tehsil Balambat, Khal, and Termergara (31%-13%) located within a range of 948-1947m elevation in the central regions with proximal CL transmissions. Hot spot and cluster and outlier analysis affirmed that Tehsil Khal was the high-risk CL foci. The Bayesian geostatistical analysis revealed high temperature, less altitude, and annual precipitation as important risk factors. An increasing trend in CL transmission has become evident, affecting both genders and <20 years old children. GIS resolute the concealed CL hubs in the least elevated central regions which warrant the control strategies to restrict future epidemics.

Epidemiological profile and lethality of visceral leishmaniasis/human immunodeficiency virus co-infection in an endemic area in Northeast Brazil

INTRODUCTION

The association of visceral leishmaniasis (VL) and human immunodeficiency virus (HIV) infection is a concern worldwide, and this co-infection is linked to increased lethality. The Northeast is the region that mostly reports cases of VL in Brazil. The knowledge of risk factors associated with VL/HIV co-infection and its impact on lethality is extremely important.

METHODS

The present study analyzed the epidemiologic features of cases with VL/HIV co-infection in the state of Pernambuco, Northeast of Brazil, from 2014 to 2018.

RESULTS

There were 858 and 11,514 reported cases of VL and HIV infection, respectively. The average incidences of VL and HIV infection were 1.82 and 24.4/100,000 inhabitants, respectively. Of all reported cases of VL, 4.9% (42/858) also had HIV infection. There was an inverse spatial association between VL and HIV infection incidences. The lethality rates of VL, HIV infection, and co-infection were 9.9%, 26.1%, and 16.6%, respectively. Most of the patients were males and lived in urban areas. The cases of VL mostly occurred in children aged below 10 years, whereas the cases of HIV infection and VL/HIV co-infection were primarily observed in adults between 20 years and 39 years old.

CONCLUSIONS

We defined the profile and areas with most cases of co-infection and found that the lethality of VL with co-infection increased in the current period. These findings contribute to applying efforts with a greater focus in these identified populations to prevent future deaths.

An investigation of the effects of environmental and ecologic factors on cutaneous leishmaniasis in the old world: a systematic review study

OBJECTIVES

Leishmaniasis is a neglected and widespread parasitic disease that can lead to serious health problems. The current review study aimed to synthesize the relationship between ecologic and environmental factors (e.g., weather conditions, climatology, temperature and topology) and the incidence of cutaneous leishmaniasis (CL) in the Old World.

CONTENT

A systematic review was conducted based on English, and Persian articles published from 2015 to 2020 in PubMed/Medline, Science Direct, Web of Science and Google Scholar. Keywords used to search articles were leishmaniasis, environmental factors, weather condition, soil, temperature, land cover, ecologic* and topogr*. All articles were selected and assessed for eligibility according to the titles or abstracts. The quality screening process of articles was carried out by two independent authors. The selected articles were checked according to the inclusion and exclusion criteria.

SUMMARY AND OUTLOOK

A total of 827 relevant records in 2015-2020 were searched and after evaluating the articles, 23 articles met the eligibility criteria; finally, 14 full-text articles were included in the systematic review. Two different categories of ecologic/environmental factors (weather conditions, temperature, rainfall/precipitation and humidity) and land characteristics (land cover, slope, elevation and altitude, earthquake and cattle sheds) were the most important factors associated with CL incidence.

CONCLUSIONS

Temperature and rainfall play an important role in the seasonal cycle of CL as many CL cases occurred in arid and semiarid areas in the Old World. Moreover, given the findings of this study regarding the effect of weather conditions on CL, it can be concluded that designing an early warning system is necessary to predict the incidence of CL based on different weather conditions.

American cutaneous leishmaniasis associated with degradation of native forest, regardless of economic, social and infrastructure vulnerability

American cutaneous leishmaniasis (ACL) is a notifiable dermatozoonosis with relevant morbidity. The present study aimed to evaluate the epidemiological aspects of cases of ACL reported in Northern Paraná (2007-2016), as well as to georeference and analyse the influence of economic, social and environmental variables. Data from ACL notification forms were obtained and the patients' houses were georeferenced. Descriptive statistics, calculations of disease incidence and proportion of vegetation cover by municipality, spatial analysis, multiple linear regression and vulnerability analysis by census sector (CS) were performed. One thousand four hundred fifty-one cases of ACL were reported in the 89 municipalities of four regional health (RH). The average incidence of cases per 10,000 inhabitants was as follows: 11.58, 8.79, 4.92 and 4.03 in 18thRH, 15thRH, 16thRH and 17thRH. Peaks of incident cases were observed in 2008, 2012 and 2015. There was a statistically significant difference between the HR when comparing the proportions of the variables gender, age, education level, area of residence, clinical form, diagnostic criteria, response to treatment and drug used in case of failure. It was observed that the lower the proportion of remaining Atlantic Forest, the greater the incidence of ACL in the municipality. With regard to clusters analysis, treatment abandonment clusters were observed in the 15thRH and mucous form clusters were observed in the 15thRH, 16thRH and 17thRH. The vulnerability analysis by CS allowed us to observe a statistically significant difference in all vulnerability indicators: economic and social in 15thRH and 17thRH; home infrastructure in 15thRH and 18thRH, urban infrastructure in 15thRH and 18thRH and compound vulnerability index in 15thRH and 18thRH. However, the most vulnerable areas did not always have the highest number of cases. The data presented demonstrate that preventive and health education measures must be mainly directed to areas of greater degradation of native forest; regardless of the vulnerability situation.

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.

Epidemiological aspects and spatial patterns of human visceral leishmaniasis in Brazil

Human visceral leishmaniasis (HVL) cases are important public health problems due to their zoonotic aspect, with high rates of morbidity and mortality in Brazil. The aim of this this study was to identify spatial patterns in both rates of HVL cases in Brazilian states during the period from 2006 to 2015. This is an ecological study, using geoprocessing tools to create choropleth maps, based on secondary data from open access platforms, to identify priority areas for control actions of the disease. Data were collected in 2017 and analysed according to the global and local Moran's I, using TerraView 4.2.2 software. Similar clusters were observed in neighbouring municipalities in thematic maps of HVL, suggesting spatial similarity in the distribution of the disease in humans mainly in the North and Northeast Regions, which concentrate the states with the highest rates of HVL. Heterogeneous spatial patterns were observed in the distribution of HVL, which show municipalities that need higher priority in the intensification of disease surveillance and control strategies.

Spatial analysis and epidemiological profile of visceral leishmaniasis, northeastern Brazil: A cross-sectional study

Most visceral leishmaniasis (VL) cases reported in Brazil are from the northeast region, where the disease is strongly linked to poverty. In spite of the still existing inequalities, many social improvements were achieved in the past decades in this region, but the possible impact of these improvements on VL remains poorly investigated. We conducted a cross-sectional study coupled with a spatial analysis of VL cases notified in northeastern Brazil from 2007 to 2017. In total, 21,703 cases were reported during this period, with an annual incidence of 3.6 cases per 100,000 inhabitants. Children under 10 years old and males were more affected, and most cases were from urban areas. Living in municipalities situated in the Cerrado, Amazon or, to a lesser extent, in the Caatinga biomes was a risk factor for VL. This study indicates that the epidemiological profile of VL patients remained unchanged in northeastern Brazil, suggesting that social improvements achieved in this region were not enough to mitigate the risk of this disease among the most affected populations.

Canine serological survey and dog culling ant its relationship with human visceral leishmaniasis in an endemic urban area

BACKGROUND

Visceral leishmaniasis is an important but neglected disease that is spreading and is highly lethal when left untreated. This study sought to measure the Leishmania infantum seroprevalence in dogs, the coverage of its control activities (identification of the canine reservoir by serological survey, dog culling and insecticide spraying) and to evaluate its relationship with the occurrence of the disease in humans in the municipalities of Araçatuba and Birigui, state of São Paulo, Brazil.

METHODS

Information from 2006 to 2015 was georeferenced for each municipality and modeling was performed for the two municipalities together. To do this, latent Gaussian Bayesian models with the incorporation of a spatio-temporal structure and Poisson distribution were used. The Besag-York-Mollie models were applied for random spatial effects, as also were autoregressive models of order 1 for random temporal effects. The modeling was performed using the INLA (Integrated Nested Laplace Approximations) deterministic approach, considering both the numbers of cases as well as the coverage paired year by year and lagged at one and two years.

RESULTS

Control activity coverage was observed to be generally low. The behavior of the temporal tendency in the human disease presented distinct patterns in the two municipalities, however, in both the tendency was to decline. The canine serological survey presented as a protective factor only in the two-year lag model.

CONCLUSIONS

The canine serological coverage, even at low intensity, carried out jointly with the culling of the positive dogs, suggested a decreasing effect on the occurrence of the disease in humans, whose effects would be seen two years after it was carried out.

Spatial dynamics and socioeconomic factors correlated with American cutaneous leishmaniasis in Pernambuco, Brazil from 2008 to 2017

INTRODUCTION:

American cutaneous leishmaniasis (ACL) is a public health problem and has been associated with country’s territory. We aimed to analyze the spatial dynamics and socioeconomic factors correlated to the incidence of ACL in Pernambuco, Brazil from 2008 to 2017.

METHODS:

A cross-sectional, ecological study was conducted in the Brazilian municipalities. Patient data were obtained from the Health Hazard Notification System (SINAN); indicators and incidence for the total period and for quinquennium were obtained. Socioeconomic factors were analyzed to evaluate the association between the incidence of ACL and presence of bathroom and running water, garbage collection availability, inadequate water supply, sanitation, rural population, per capita income, and vulnerability to poverty. Spatial analysis considered the gross incidence; the Bayesian local empirical method and Moran spatial autocorrelation index were applied using Terra View and QGIS.

RESULTS:

The incidence of ACL reduced (0.29/100,000 inhabitants per year). Individuals with ACL were young adults (30.3%), men (60.2%), brown skinned (62.9%), rural residents (70.6%), and less educated (46.7%); had autochthonous transmission (78.8%); developed the cutaneous form (97.2%); had evolution to cure (82.7%); and were diagnosed using the clinical epidemiological criterion (70.5%). ACL occurred in the large part of the state and showed heterogeneous distribution, with persistence of two high priority intervention clusters covering Health Regions I, II, III, IV, and XII.

CONCLUSIONS:

Spatial analysis and epidemiological indicators complement each other. The combination of these methods can improve the understanding on ACL occurrence, which will help subsidize planning and enhance the quality and effectiveness of healthcare interventions.

Construction of polluted aerosol in accumulation that affects the incidence of lung cancer

Background

This model demonstrated the correlation between lung cancer incidences and the parts of ambient air pollution according to the National Aeronautics and Space Administration (NASA)'s high resolution technology satellites.

Methods

Chemical type of aerosols was investigated by the Aerosol Diagnostics Model such as black carbon, mineral dust, organic carbon, sea-salt and SO4. The model investigated associations between the six year accumulation of each aerosol and lung cancer incidence by Bayesian hierarchical spatio-temporal model. Which also represented integrated geophysical parameters.

Results

In analyses of accumulated chemical aerosol component from 2010 – 2016, the incidence rate ratio (IRR) of patients in 2017 were estimated. We observed a significant increasing risk for organic carbon exposure (IRR 1.021, 95%CI 1.020–1.022), SO₄, (IRR 1.026, 95% CI 1.025–1.028) and dust, (IRR 1.061, 95% CI 1.058–1.064). There was also suggestion of an increased risk with, every 1 ug/m³ increase in organic carbon compound is associated with 21% increased risk of lung cancer, whereas a 26% excess risk of cancer per 1 ug/m³ increase in mean SO₄ and 61% increased risk of lung cancer for dust levels. The other variables were the negative IRR which did not increase the risk of the exposed group.

Conclusion

With our results, this process can determine that organic carbon, SO₄ and dust was significantly associated with the elevated risk of lung cancer.

Temporal lagged relationship between a vegetation index and cutaneous leishmaniasis cases in Colombia: an analysis implementing a distributed lag nonlinear model

Cutaneous leishmaniasis is a neglected tropical disease with a strong environmental component. The aim of this research was to implement a distributed lag nonlinear model to explore the temporal lagged relationship between a vegetation index and cutaneous leishmaniasis cases. In this ecological study, a time series of weekly cases of cutaneous leishmaniasis reported between 2007 and 2016 in the five municipalities in Colombia with the most cases of the disease and a vegetation index was analyzed. During the study period, a total of 16,321 cases were reported in these five municipalities. Two municipalities showed a lagged nonlinear positive association between the risk of occurrence of new cases and the magnitude of the vegetation index; two municipalities showed a negative association; and in the remaining municipality, the risk was associated with the vegetation index but its confidence interval was not significant. Our results show different patterns and magnitudes of the lagged relationship between the vegetation index and cutaneous leishmaniasis cases and suggest the possibility of using the lag pattern of the vegetation index in the development of an early warning system where a lagged positive relationship is identified.

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.

Space-time analysis of the incidence of human visceral leishmaniasis (VL) and prevalence of canine VL in a municipality of southeastern Brazil: Identification of priority areas for surveillance and control

Human and canine visceral leishmaniasis (HVL and CVL, respectively) represent serious public health issues in Brazil. The surveillance and control measures currently employed have had limited effect in impeding the territorial expansion of the disease and in reducing the number of cases. We have investigated the space-time distribution of HVL incidence rates and CVL prevalence in the coverage areas of the 148 primary healthcare units in Belo Horizonte (MG, Brazil) during a 6-year period in order to identify those that should be prioritized for disease control actions. Data were smoothed using the empirical Bayes method and analyzed by space-time scanning and application of univariate global Moran's I index and local indicators of spatial association (LISA) statistics to identify spatial autocorrelations. Point data of CVL were analyzed using the Kernel method. Bivariate global Moran's I and LISA techniques were employed to identify spatial correlations between HVL and CVL. Based on our results, we were able to formulate two proposals for establishing the prioritization of coverage areas, namely: (i) classification of maximum priority areas as identified by bivariate LISA for HVL and CVL, and (ii) combination of maximum priority areas with high priority areas as identified by univariate LISA for HVL. According to our proposals, 27 coverage areas in Belo Horizonte were categorized as maximum priority and a further 13 were classified as high priority. Our proposals, which are based on practical, feasible and inexpensive statistical tools, will contribute to a better understanding of VL distribution in urban settings and improving the efficiency of governmental control programs.

Ecological niche modelling for predicting the risk of cutaneous leishmaniasis in the Neotropical moist forest biome

A major challenge of eco-epidemiology is to determine which factors promote the transmission of infectious diseases and to establish risk maps that can be used by public health authorities. The geographic predictions resulting from ecological niche modelling have been widely used for modelling the future dispersion of vectors based on the occurrence records and the potential prevalence of the disease. The establishment of risk maps for disease systems with complex cycles such as cutaneous leishmaniasis (CL) can be very challenging due to the many inference networks between large sets of host and vector species, with considerable heterogeneity in disease patterns in space and time. One novelty in the present study is the use of human CL cases to predict the risk of leishmaniasis occurrence in response to anthropogenic, climatic and environmental factors at two different scales, in the Neotropical moist forest biome (Amazonian basin and surrounding forest ecosystems) and in the surrounding region of French Guiana. With a consistent data set never used before and a conceptual and methodological framework for interpreting data cases, we obtained risk maps with high statistical support. The predominantly identified human CL risk areas are those where the human impact on the environment is significant, associated with less contributory climatic and ecological factors. For both models this study highlights the importance of considering the anthropogenic drivers for disease risk assessment in human, although CL is mainly linked to the sylvatic and peri-urban cycle in Meso and South America.

Ecological niche models for sand fly species and predicted distribution of Lutzomyia longipalpis (Diptera: Psychodidae) and visceral leishmaniasis in Bahia state, Brazil

Visceral leishmaniasis is a public health problem in Brazil. This disease is endemic in most of Bahia state, with increasing reports of cases in new areas. Ecological niche models (ENM) can be used as a tool for predicting potential distribution for disease, vectors, and to identify risk factors associated with their distribution. In this study, ecological niche models (ENMs) were developed for visceral leishmaniasis (VL) cases and 12 sand fly species captured in Bahia state. Sand fly data was collected monthly by CDC light traps from July 2009 to December 2012. MODIS satellite imagery was used to calculate NDVI, NDMI, and NDWI vegetation indices, MODIS day and night land surface temperature (LST), enhanced vegetation index (EVI), and 19 Bioclim variables were used to develop the ENM using the maximum entropy approach (Maxent). Mean diurnal range was the variable that most contributed to all the models for sand flies, followed by precipitation in wettest month. For Lutzomyia longipalpis (L. longipalpis), annual precipitation, precipitation in wettest quarter, precipitation in wettest month, and NDVI were the most contributing variables. For the VL model, the variables that contributed most were precipitation in wettest month, annual precipitation, LST day, and temperature seasonality. L. longipalpis was the species with the widest potential distribution in the state. The identification of risk areas and factors associated with this distribution is fundamental to prioritize resource allocation and to improve the efficacy of the state's program for surveillance and control of VL.

Current Visceral Leishmaniasis Research: A Research Review to Inspire Future Study

Visceral leishmaniasis (VL), one of the deadliest parasitic diseases in the world, causes more than 50,000 human deaths each year and afflicts millions of people throughout South America, East Africa, South Asia, and Mediterranean Region. In 2015 the World Health Organization classified VL as a neglected tropical disease (NTD), prompting concentrated study of the VL epidemic using mathematical and simulation models. This paper reviews literature related to prevalence and prevention control strategies. More than thirty current research works were reviewed and classified based on VL epidemic study methods, including modeling approaches, control strategies, and simulation techniques since 2013. A summarization of these technical methods, major findings, and contributions from existing works revealed that VL epidemic research efforts must improve in the areas of validating and verifying VL mathematical models with real-world epidemic data. In addition, more dynamic disease control strategies must be explored and advanced simulation techniques must be used to predict VL pandemics.

Role of environmental, climatic risk factors and livestock animals on the occurrence of cutaneous leishmaniasis in newly emerging focus in Iran

INTRODUCTION

Occurrence of leishmaniasis is affected by various biological and environmental factors. Kohgiluye and Boyerahmad (K-B) province is an emerging focus of cutaneous leishmaniasis (CL) in Southwest Iran.

SUBJECTS AND METHODS

To elucidate some angles of occurrence of CL in this province, climatic and environmental factors and close proximity to livestock were studied by univariate and two multivariate logistic regression models. The dwelling addresses of 275 CL patients were obtained from Health Centers records for a 5 years period. The effect of mean annual temperature, minimum mean annual temperature, maximum mean annual temperature, mean annual rainfall, slope, elevation, land covers and close proximity to cattle and sheep/goat sheds on the occurrence of CL were analysed using geographical information systems (GIS) approach.

RESULTS

CL occurred in all counties with the most cases in Northwest, West and South semi-arid and warm regions. Land cover, slope, elevation and close proximity to cattle sheds, were the most effective factors. Urban, dry farm and thin rangeland were found as the most important land covers. Slope and elevation decreased the probability of disease. Close proximity to cattle sheds notably increased the chance of CL. The importance of other factors such as rainfall, temperature and close proximity to sheep/goat sheds only were shown when their effects were evaluated independently from other factors. So regions with urban, dry farm and thin rangeland covers with lower slope and altitude where in close proximity of cattle sheds seems to be potentially most high risk areas.

CONCLUSION

Distribution of CL cases is influenced by combination of environmental, ecological factors and close proximity to livestock sheds but control programs should be focused on cities and villages in the above-mentioned most high risk regions.

Changes in the epidemiology of visceral leishmaniasis in Brazil from 2001 to 2014

INTRODUCTION

Visceral leishmaniasis (VL) is a neglected disease, with territorial expansion and regional differences in Brazil that require explanation. This study aimed to describe changes in the epidemiology of VL in Brazil from 2001 to 2014.

METHODS

The incidence rates, sociodemographic and clinical data, and case evolution were subgrouped from 2001 to 2006 and from 2007 to 2014 and presented descriptively. Spatial distribution of disease incidence rates and changes in the spatial and temporal pattern were examined.

RESULTS

In total, 47,859 VL cases were reported in Brazil between 2001 and 2014, with predominance in the Northeast macroregion (55%), though the incidence rate in this region declined between the two study periods. The State of Tocantins had the highest crude rate (26.2/100,000 inhabitants), which was responsible for VL increasing in the North macroregion. VL predominated in the urban zone (70%), in children under 4 years (34%); however, an increase in the incidence of VL in adults older than 40 years was identified, with 12.3% and 31% in the first and second period, respectively. The mapping of crude rates and autochthonous canine cases showed territorial expansion. The temporal distribution of VL was consistent in Brazil in general, with no pattern observed, but regional differences were found.

CONCLUSIONS

The incidence of VL is increasing in Brazil. In addition to the State of Tocantins, which had the highest rate, new outbreaks of VL have occurred in the South macroregion of Brazil with small decreases identified in the incidence rate in the Northeast.

How will climate change pathways and mitigation options alter incidence of vector-borne diseases? A framework for leishmaniasis in South and Meso-America

The enormous global burden of vector-borne diseases disproportionately affects poor people in tropical, developing countries. Changes in vector-borne disease impacts are often linked to human modification of ecosystems as well as climate change. For tropical ecosystems, the health impacts of future environmental and developmental policy depend on how vector-borne disease risks trade off against other ecosystem services across heterogeneous landscapes. By linking future socio-economic and climate change pathways to dynamic land use models, this study is amongst the first to analyse and project impacts of both land use and climate change on continental-scale patterns in vector-borne diseases. Models were developed for cutaneous and visceral leishmaniasis in the Americas-ecologically complex sand fly borne infections linked to tropical forests and diverse wild and domestic mammal hosts. Both diseases were hypothesised to increase with available interface habitat between forest and agricultural or domestic habitats and with mammal biodiversity. However, landscape edge metrics were not important as predictors of leishmaniasis. Models including mammal richness were similar in accuracy and predicted disease extent to models containing only climate and land use predictors. Overall, climatic factors explained 80% and land use factors only 20% of the variance in past disease patterns. Both diseases, but especially cutaneous leishmaniasis, were associated with low seasonality in temperature and precipitation. Since such seasonality increases under future climate change, particularly under strong climate forcing, both diseases were predicted to contract in geographical extent to 2050, with cutaneous leishmaniasis contracting by between 35% and 50%. Whilst visceral leishmaniasis contracted slightly more under strong than weak management for carbon, biodiversity and ecosystem services, future cutaneous leishmaniasis extent was relatively insensitive to future alternative socio-economic pathways. Models parameterised at narrower geographical scales may be more sensitive to land use pattern and project more substantial changes in disease extent under future alternative socio-economic pathways.

Spatial and temporal trends of visceral leishmaniasis by mesoregion in a southeastern state of Brazil, 2002-2013

BACKGROUND

Visceral leishmaniasis (VL) is expanding in Brazil and in other South American countries, a process that has been associated with the urbanization of the disease. This study analyzes the spatial and temporal distribution of VL in the Brazilian state of Minas Gerais and identifies the areas with higher risks of transmission.

METHODOLOGY

An ecological study with spatial and time series analyzes of new confirmed cases of VL notified to the Brazilian Notifiable Disease Information System between 2002 and 2013, considering the 12 mesoregions of Minas Gerais. Two complementary methodologies were used: thematic maps of incidence and Poisson (log-linear) generalized linear model. Thematic maps using crude and smoothed cumulative incidences were generated for four trienniums. Poisson Regression measured the variation of the average number of cases from one year to the following, for each mesoregion.

PRINCIPAL FINDINGS

The 5,778 cases analyzed revealed a heterogeneous spatial and temporal distribution of VL in Minas Gerais. Six mesoregions (Central Mineira, Jequitinhonha, Metropolitan area of Belo Horizonte, Northwest of Minas, North of Minas, and Vale do Rio Doce) were responsible for the expansion and maintenance of VL, with incidence rates as high as 26/100,000 inhabitants. The Vale do Rio Doce and Jequitinhonha mesoregions showed a considerable increase in the incidence rates in the last period studied. The other six mesoregions reported only sporadic cases and presented low and unsteady incidence rates, reaching a maximum of 1.2/100,000 inhabitants.

CONCLUSIONS/SIGNIFICANCE

The results contribute to further the current understanding about the expansion of VL in Minas Gerais and may help guide actions for disease control.

A time series analysis of environmental and metrological factors impact on cutaneous leishmaniasis incidence in an endemic area of Dehloran, Iran

The aim of this study was to investigate the relationship between the environmental and metrological variables and cutaneous leishmaniasis (CL) transmission and its prediction in a region susceptible to this disease prevalence using a time series model. The accurate locations of 4437 CL diagnosed from 2011 to 2015 were obtained to be used in the time series model. Temperature, number of days with temperature over 30 °C, and number of earthquake were related to CL incidence using the Seasonal Auto-correlated Integrated Moving Average (SARIMA) model according to the Box-Jenkins method. In addition, the relationship between land use and surface soil type in 500- and 1000-m radius around the CL patients were investigated. The SARIMA models showed significant associations between environmental and meteorological variables and CL incidence adjusted for seasonality and auto-correlation. The result indicated that there are need more robust preventive programs in earthquake-prone areas with high temperature and inceptisol soil type than other areas. In addition, the region with these characteristics should be considered as high-risk areas for CL prevalence.

Risk mapping of clonorchiasis in the People's Republic of China: A systematic review and Bayesian geostatistical analysis

BACKGROUND

Clonorchiasis, one of the most important food-borne trematodiases, affects more than 12 million people in the People's Republic of China (P.R. China). Spatially explicit risk estimates of Clonorchis sinensis infection are needed in order to target control interventions.

METHODOLOGY

Georeferenced survey data pertaining to infection prevalence of C. sinensis in P.R. China from 2000 onwards were obtained via a systematic review in PubMed, ISI Web of Science, Chinese National Knowledge Internet, and Wanfang Data from January 1, 2000 until January 10, 2016, with no restriction of language or study design. Additional disease data were provided by the National Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention in Shanghai. Environmental and socioeconomic proxies were extracted from remote-sensing and other data sources. Bayesian variable selection was carried out to identify the most important predictors of C. sinensis risk. Geostatistical models were applied to quantify the association between infection risk and the predictors of the disease, and to predict the risk of infection across P.R. China at high spatial resolution (over a grid with grid cell size of 5×5 km).

PRINCIPAL FINDINGS

We obtained clonorchiasis survey data at 633 unique locations in P.R. China. We observed that the risk of C. sinensis infection increased over time, particularly from 2005 onwards. We estimate that around 14.8 million (95% Bayesian credible interval 13.8-15.8 million) people in P.R. China were infected with C. sinensis in 2010. Highly endemic areas (≥ 20%) were concentrated in southern and northeastern parts of the country. The provinces with the highest risk of infection and the largest number of infected people were Guangdong, Guangxi, and Heilongjiang.

CONCLUSIONS/SIGNIFICANCE

Our results provide spatially relevant information for guiding clonorchiasis control interventions in P.R. China. The trend toward higher risk of C. sinensis infection in the recent past urges the Chinese government to pay more attention to the public health importance of clonorchiasis and to target interventions to high-risk areas.

Risk analysis and prediction of visceral leishmaniasis dispersion in São Paulo State, Brazil

Visceral leishmaniasis (VL) is an important neglected disease caused by a protozoan parasite, and represents a serious public health problem in many parts of the world. It is zoonotic in Europe and Latin America, where infected dogs constitute the main domestic reservoir for the parasite and play a key role in VL transmission to humans. In Brazil this disease is caused by the protozoan Leishmania infantum chagasi, and is transmitted by the sand fly Lutzomyia longipalpis. Despite programs aimed at eliminating infection sources, the disease continues to spread throughout the Country. VL in São Paulo State, Brazil, first appeared in the northwestern region, spreading in a southeasterly direction over time. We integrate data on the VL vector, infected dogs and infected human dispersion from 1999 to 2013 through an innovative spatial temporal Bayesian model in conjunction with geographic information system. This model is used to infer the drivers of the invasion process and predict the future progression of VL through the State. We found that vector dispersion was influenced by vector presence in nearby municipalities at the previous time step, proximity to the Bolívia-Brazil gas pipeline, and high temperatures (i.e., annual average between 20 and 23°C). Key factors affecting infected dog dispersion included proximity to the Marechal Rondon Highway, high temperatures, and presence of the competent vector within the same municipality. Finally, vector presence, presence of infected dogs, and rainfall (approx. 270 to 540mm/year) drove the dispersion of human VL cases. Surprisingly, economic factors exhibited no noticeable influence on disease dispersion. Based on these drivers and stochastic simulations, we identified which municipalities are most likely to be invaded by vectors and infected hosts in the future. Prioritizing prevention and control strategies within the identified municipalities may help halt the spread of VL while reducing monitoring costs. Our results contribute important knowledge to public and animal health policy planning, and suggest that prevention and control strategies should focus on vector control and on blocking contact between vectors and hosts in the priority areas identified to be at risk.

Dispersal of Lutzomyia longipalpis and expansion of canine and human visceral leishmaniasis in São Paulo State, Brazil

Visceral leishmaniasis (VL), a neglected disease, is a serious public health problem that affects millions of people worldwide. The objectives of the study were to evaluate the sensitivity of Lutzomyia longipalpis and canine VL (CVL) autochthony early detection and describe the spatial and temporal dispersal of vector and expansion of VL in a Brazilian state. We obtained data on the leishmaniasis vector and VL cases in São Paulo State (SP), Brazil, from the Division of Endemic Disease Control and from the Epidemiological Surveillance Center of the São Paulo State Department of Health. Data were analyzed for 645 municipalities and 63 microregions and presented as thematic and flow maps. Following the verified presence of L. longipalpis in Araçatuba in 1997, the first autochthonous cases of canine VL (CVL) (1998) and of human VL (HVL) (1999) in São Paulo were reported, both in Araçatuba. From 1997 to 2014, the urban presence of the leishmaniasis vector was verified in 167 (25.9%) municipalities with cases of CVL reported in 108 (16.7%) and cases of HVL in 84 (13%). The sensitivities for vector presence early detection in relation to the identification of CVL and HVL autochthony were, respectively, equal to 76.4 and 92.5%. The sensitivity for CVL autochthony early detection in relation to the HVL autochthony identification was 75.8%. Vector dispersal and expansion of CVL and HVL were from the northwest to the southeast of the state, primarily flanking the Marechal Rondon highway at a constant rate of progression of 10, seven, and six new municipalities affected per year, respectively. We concluded that the sensitivity for vector presence and CVL autochthony presented reasonable accuracy and most of the time the vector presence and, specially, the CVL and HVL autochthony were identified in the main cities of the microregions of SP. Vector dispersal and expansion of VL started in 1997 near the state border of SP with the state of Mato Grosso do Sul. It has advanced from the northwest to the southeast flanking the Marechal Rondon highway at an arithmetic progression rate outward from the main cities of the microregions. Autochthonous cases of CVL and HVL emerged in SP, in general, after the verified presence of L. longipalpis.

In Vitro and In Vivo Activities of 2,3-Diarylsubstituted Quinoxaline Derivatives against Leishmania amazonensis

Leishmaniasis is endemic in 98 countries and territories worldwide. The therapies available for leishmaniasis have serious side effects, thus prompting the search for new therapies. The present study investigated the antileishmanial activities of 2,3-diarylsubstituted quinoxaline derivatives against Leishmania amazonensis The antiproliferative activities of 6,7-dichloro-2,3-diphenylquinoxaline (LSPN329) and 2,3-di-(4-methoxyphenyl)-quinoxaline (LSPN331) against promastigotes and intracellular amastigotes were assessed, and the cytotoxicities of LSPN329 and LSPN331 were determined. Morphological and ultrastructural alterations were examined by electron microscopy, and biochemical alterations, reflected by the mitochondrial membrane potential (ΔΨm), mitochondrial superoxide anion (O2·(-)) concentration, the intracellular ATP concentration, cell volume, the level of phosphatidylserine exposure on the cell membrane, cell membrane integrity, and lipid inclusions, were evaluated. In vivo antileishmanial activity was evaluated in a murine cutaneous leishmaniasis model. Compounds LSPN329 and LSPN331 showed significant selectivity for promastigotes and intracellular amastigotes and low cytotoxicity. In promastigotes, ultrastructural alterations were observed, including an increase in lipid inclusions, concentric membranes, and intense mitochondrial swelling, which were associated with hyperpolarization of ΔΨm, an increase in the O2·(-) concentration, decreased intracellular ATP levels, and a decrease in cell volume. Phosphatidylserine exposure and DNA fragmentation were not observed. The cellular membrane remained intact after treatment. Thus, the multifactorial response that was responsible for the cellular collapse of promastigotes was based on intense mitochondrial alterations. BALB/c mice treated with LSPN329 or LSPN331 showed a significant decrease in lesion thickness in the infected footpad. Therefore, the antileishmanial activity and mitochondrial mechanism of action of LSPN329 and LSPN331 and the decrease in lesion thickness in vivo brought about by LSPN329 and LSPN331 make them potential candidates for new drug development for the treatment of leishmaniasis.

Co-endemicity of Pulmonary Tuberculosis and Intestinal Helminth Infection in the People's Republic of China

Both pulmonary tuberculosis (PTB) and intestinal helminth infection (IHI) affect millions of individuals every year in China. However, the national-scale estimation of prevalence predictors and prevalence maps for these diseases, as well as co-endemic relative risk (RR) maps of both diseases' prevalence are not well developed. There are co-endemic, high prevalence areas of both diseases, whose delimitation is essential for devising effective control strategies. Bayesian geostatistical logistic regression models including socio-economic, climatic, geographical and environmental predictors were fitted separately for active PTB and IHI based on data from the national surveys for PTB and major human parasitic diseases that were completed in 2010 and 2004, respectively. Prevalence maps and co-endemic RR maps were constructed for both diseases by means of Bayesian Kriging model and Bayesian shared component model capable of appraising the fraction of variance of spatial RRs shared by both diseases, and those specific for each one, under an assumption that there are unobserved covariates common to both diseases. Our results indicate that gross domestic product (GDP) per capita had a negative association, while rural regions, the arid and polar zones and elevation had positive association with active PTB prevalence; for the IHI prevalence, GDP per capita and distance to water bodies had a negative association, the equatorial and warm zones and the normalized difference vegetation index had a positive association. Moderate to high prevalence of active PTB and low prevalence of IHI were predicted in western regions, low to moderate prevalence of active PTB and low prevalence of IHI were predicted in north-central regions and the southeast coastal regions, and moderate to high prevalence of active PTB and high prevalence of IHI were predicted in the south-western regions. Thus, co-endemic areas of active PTB and IHI were located in the south-western regions of China, which might be determined by socio-economic factors, such as GDP per capita.

Oleanolic acid (OA) as an antileishmanial agent: Biological evaluation and in silico mechanistic insights

Although a worldwide health problem, leishmaniasis is considered a highly neglected disease, lacking efficient and low toxic treatment. The efforts for new drug development are based on alternatives such as new uses for well-known drugs, in silico and synthetic studies and naturally derived compounds. Oleanolic acid (OA) is a pentacyclic triterpenoid widely distributed throughout the Plantae kingdom that displays several pharmacological activities. OA showed potent leishmancidal effects in different Leishmania species, both against promastigotes (IC(50 L. braziliensis) 30.47 ± 6.35 μM; IC(50 L. amazonensis) 40.46 ± 14.21 μM; IC(50 L. infantum) 65.93 ± 15.12 μM) and amastigotes (IC(50 L. braziliensis) 68.75 ± 16.55 μM; IC(50 L. amazonensis) 38.45 ± 12.05 μM; IC(50 L. infantum) 64.08 ± 23.52 μM), with low cytotoxicity against mouse peritoneal macrophages (CC(50) 235.80 ± 36.95 μM). Moreover, in silico studies performed to evaluate OA molecular properties and to elucidate the possible mechanism of action over the Leishmania enzyme sterol 14α-demethylase (CYP51) suggested that OA interacts efficiently with CYP51 and could inhibit the ergosterol synthesis pathway. Collectively, these data indicate that OA is a good candidate as leading compound for the development of a new leishmaniasis treatment.

Model-Based Geostatistical Mapping of the Prevalence of Onchocerca volvulus in West Africa

BACKGROUND

The initial endemicity (pre-control prevalence) of onchocerciasis has been shown to be an important determinant of the feasibility of elimination by mass ivermectin distribution. We present the first geostatistical map of microfilarial prevalence in the former Onchocerciasis Control Programme in West Africa (OCP) before commencement of antivectorial and antiparasitic interventions.

METHODS AND FINDINGS

Pre-control microfilarial prevalence data from 737 villages across the 11 constituent countries in the OCP epidemiological database were used as ground-truth data. These 737 data points, plus a set of statistically selected environmental covariates, were used in a Bayesian model-based geostatistical (B-MBG) approach to generate a continuous surface (at pixel resolution of 5 km x 5km) of microfilarial prevalence in West Africa prior to the commencement of the OCP. Uncertainty in model predictions was measured using a suite of validation statistics, performed on bootstrap samples of held-out validation data. The mean Pearson's correlation between observed and estimated prevalence at validation locations was 0.693; the mean prediction error (average difference between observed and estimated values) was 0.77%, and the mean absolute prediction error (average magnitude of difference between observed and estimated values) was 12.2%. Within OCP boundaries, 17.8 million people were deemed to have been at risk, 7.55 million to have been infected, and mean microfilarial prevalence to have been 45% (range: 2-90%) in 1975.

CONCLUSIONS AND SIGNIFICANCE

This is the first map of initial onchocerciasis prevalence in West Africa using B-MBG. Important environmental predictors of infection prevalence were identified and used in a model out-performing those without spatial random effects or environmental covariates. Results may be compared with recent epidemiological mapping efforts to find areas of persisting transmission. These methods may be extended to areas where data are sparse, and may be used to help inform the feasibility of elimination with current and novel tools.