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

Spatio-temporal analysis of American Tegumentary Leishmaniasis incidences in the Brazilian state of Amazonas: 2011 to 2022

This study aimed to conduct a spatio-temporal analysis of tegumentary leishmaniasis occurrences in the Amazonas state, Brazil. An ecological study encompassing time series and spatial analysis was performed, exploring the geographic distribution and temporal trends of American Tegumentary Leishmaniasis (ATL) in Amazonas between 2011 and 2022. Secondary data extracted from the Department of Informatics of the Unified Health System (DATASUS) were utilized for this analysis. The study evaluated the relationship between disease cases and environmental/climatic variables (deforestation, temperature, precipitation, and relative humidity). Over the study period, 19,730 cases of tegumentary leishmaniasis were recorded, averaging an incidence of 41.4/100,000 inhabitants across the 62 municipalities of Amazonas state. Disease intensity varied with seasons. Generally, Amazonas state displayed a declining trend in ATL cases. However, certain municipalities, notably Rio Preto da Eva and Presidente Figueiredo, exhibited high incidence rates, while Canutama, Envira, Eirunepé, and Pauini municipalities demand closer attention due to their demonstrated increasing temporal trend of ATL cases. The analysis indicated a correlation between the number of ATL cases reported and relative humidity as well as precipitation. These findings underscore the significance of tegumentary leishmaniasis as a public health issue in the region and emphasize the necessity for public initiatives aimed at preventing this endemic illness.

The Impact of Climatological Factors on the Incidence of Cutaneous Leishmaniasis (CL) in Colombian Municipalities from 2017 to 2019

Cutaneous leishmaniasis (CL) is a zoonotic disease caused by protozoa of the Leishmania genus, transmitted by vectors from the Phlebotominae subfamily. The interaction between the vector, reservoir, and parasite is susceptible to climate change. This study explores how temperature and rainfall influenced the incidence of CL in 15 Colombian municipalities between 2017 and 2019. Epidemiological data were obtained from Colombia's Instituto Nacional de Salud, while climatological data came from the Instituto de Hidrología, Meteorología y Estudios Ambientales. Using Spearman's rank correlation coefficient, we examined the relationships between monthly climatic variables and the cumulative incidence of CL, considering various lag times. The data were further analyzed using Locally Weighted Scatterplot Smoothing (LOWESS). Our findings reveal both significant positive and negative correlations, depending on locality and climate variables. LOWESS analysis indicates that while rainfall-related incidence remains stable, temperature impacts incidence in a parabolic trend. This study underscores the significant yet complex influence of climatic factors on CL incidence. The insights gained could aid public health efforts by improving predictive models and crafting targeted interventions to mitigate the disease's impact, particularly in regions vulnerable to climate variability.

Analysis of the current risk of Leishmania infantum transmission for domestic dogs in Spain and Portugal and its future projection in climate change scenarios

Canine leishmaniosis, caused by the protozoan parasite Leishmania infantum, is a cosmopolitan vector-borne zoonosis, transmitted principally by Phlebotomus perniciosus in Spain and Portugal, where it is considered an endemic disease. Ecoinformatics tools such as ecological niche models (ENM) have been successfully tested to model the distribution of the risk of infection of different parasitosis as they take into account environmental variables vital for their survival. The risk map proposed in this study combines the potential distribution of Ph. perniciosus in the Iberian Peninsula and the calculation of the infection rate of the parasite in the vector to model the risk of contracting the disease in a more realistic way. In fact, this weighting strategy improves the predictive power of the resulting model (R2 = 0.42, p = < 0.01) compared to the Ph. perniciosus ENM model alone (R2 = 0.13, p > 0.05). The places with the highest risk of transmission are the southwest and central peninsular area, as well as the Mediterranean coast, the Balearic Islands and the Ebro basin, places where the ideal habitat of Ph. perniciosus and the infection rate is also high. In the case of future projections under climate change scenarios, an increase in the risk of infection by L. infantum can be observed in most of the territory (4.5% in 2040, 71.6% in 2060 and 63% in 2080), mainly in the northern part of the peninsula. The use of ENMs and their weighting with the infection rate in Ph. perniciosus is a useful tool in predicting the risk of infection for L. infantum in dogs for a given area. In this way, a more complete model can be obtained to facilitate prevention and control.

Environmental and socio-demographic factors associated with cutaneous leishmaniasis in district Khyber, Pakistan; alarming spread of the disease to new foci

Cutaneous leishmaniasis (CL) is a sand fly-borne infection of significant public health concern in Pakistan (endemic for CL). This study aimed to scrutinize the environmental and socio-economic risk factors for CL in district Khyber (located on Pak-Afghan border), Pakistan. Clinically confirmed 2881 CL case records for (January-December) 2017 and 2020 were obtained from district hospital. In addition, a questionnaire for CL risk factors assessment was administered to 525 households (175 in 2017 and 350 in 2020) in 40 villages throughout the district in a household survey. Higher number of CL cases were recorded in 2020 (N = 1824 belonging to 90 villages) compared to 2017 (N = 1057 from 42 villages). Highest number of CL patient cases were recorded in tehsil Jamrud (N = 2248, 39.01 %), followed by Landi Kotal (N = 398, 6.91 %) and Bara (N = 235, 4.08 %). Records showed higher number of CL cases in males (N = 1,659, 57.58 %) compared to females (N = 1,222, 42.41 %). In 2017 and 2020 the disease burden peaked in January. GIS-based spatial analyses of hospital records revealed that CL cases were abundant at 294-1,916 m elevation, in agriculture and range lands. Univariate logistic regression model analysis of risk factors suggested that higher education, family size >15, knowledge of CL, having family member/s that suffered from CL in the past, knowledge about biting time of sand flies, use of mosquito spray, presence of Afghan refugees in the village/s and living in mud-made houses increased the risk of acquiring CL. The multivariable logistic regression model showed none of the risk factors to be statistically significant. Findings of the study are crucial towards effective and targeted control of CL in district Khyber.

Predicting Suitable Areas for African Swine Fever Outbreaks in Wild Boars in South Korea and Their Implications for Managing High-Risk Pig Farms

African swine fever (ASF) is a highly contagious disease affecting domestic pigs and wild boars, with no effective vaccine or treatment available. In South Korea, extensive measures have been implemented to prevent ASF transmission between wild boars and ASF spillover from wild boars to pig farm sectors, including the search for ASF-infected carcasses in mountainous forests and the installation of fences across wide areas of these forests. To determine the priority search range for infected carcasses and establish pig farm-centered quarantine measures, it is necessary to predict the specific path of ASF outbreaks in wild boars and identify pig farms at high risk of ASF spillover from wild boars. Here, we aimed to predict suitable areas and geographical paths for ASF outbreaks in wild boars using the MaxEnt model and shortest-path betweenness centrality analysis. The analysis identified a high frequency of ASF outbreaks in areas with a suitability value ≥0.4 on the suitability map and in areas within a 1.8 km range from the path on the shortest-path map, indicating these areas were high-risk zones for ASF outbreaks. Among the 5063 pig farms analyzed, 37 were in the high-risk zone on the suitability map, 499 were in the high-risk zone on the shortest-path map, and 9 were in both risk zones. Of the 51 pig farm sectors with a dense distribution of pig farms (kernel density ≥ 8), 25 sectors were in contact with or partially overlapped the high risk zone on the suitability map, 18 sectors were located within the high risk zone on the shortest-path map, and 14 sectors were located within both risk zones. These findings aided in determining the priority range for searches for wild boar carcasses and enabled the establishment of preemptive ASF prevention measures around the pig farming sectors that are at risk of ASF spillover from wild boars.

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.

Diversity and geographical distribution of Leishmania species and the emergence of Leishmania (Leishmania) infantum and L. (Viannia) panamensis in Central-Western Venezuela

Transmission of cutaneous leishmaniasis in Venezuela reveals diverse and changing epidemiological landscapes, as well as a spectrum of clinical phenotypes presumed to be linked to a variety of Leishmania species. Central-western Venezuela constitutes one of the highest endemic epicenters in the country, yet updated molecular epidemiological information is still lacking. Therefore, in this study we aimed to characterize the landscape of circulating Leishmania species across central-western Venezuela through the last two decades, performed comparisons of haplotype and nucleotide diversity, and built a geospatial map of parasite species distribution. A total of 120 clinical samples were collected from patients across the cutaneous disease spectrum, retrieving parasitic DNA, and further characterizing by PCR and sequencing of the HSP70 gene fragment. This data was later collated with further genetic, geospatial and epidemiological analyses. A peculiar pattern of species occurrence including Leishmania (Leishmania) amazonensis (77.63% N=59), Leishmania (Leishmania) infantum (14.47% N=11), Leishmania (Viannia) panamensis (5.26% N=4) and Leishmania (Viannia) braziliensis (2.63% N=2) was revealed, also highlighting a very low genetic diversity amongst all analyzed sequences. Geographical distribution showed that most cases are widely distributed across the greater urban-sub urban area of the Irribaren municipality. L.(L.) amazonensis appears to be widely dispersed throughout Lara state. Statistical analyses failed to reveal significance for any comparisons, leading to conclude a lack of association between the infective Leishmania species and clinical phenotypes. To the best of our knowledge, this is an unprecedented study which addresses comprehensively the geographical distribution of Leishmania species in central-western Venezuela throughout the last two decades, and the first to incriminate L. (L.) infantum as an etiologic agent of cutaneous leishmaniasis in this region. Our findings support that Leishmania endemism in central-western Venezuela is caused mainly by L.(L.) amazonensis. Future studies are needed to unveil additional details on the ecological intricacies and transmission aspects of leishmaniasis (i.e. sampling phlebotomines and mammals) and to adopt adequate public health prevention and control strategies and mitigate disease impact in this endemic region.

First report of Leishmania (Mundinia) martiniquensis in South American territory and confirmation of Leishbunyavirus infecting this parasite in a mare

BACKGROUND

Epidemiological data related to leishmaniases or Leishmania infection in horses are scarce. However, studies carried out in different regions in the world showed equids parasitised by Leishmania braziliensis, L. infantum and L. martiniquensis.

OBJECTIVES

Identify the Leishmania species causing cutaneous leishmaniasis in a mare, living in Rio de Janeiro State (Brazil), and search the presence of Leishmania viruses in the isolated parasite.

METHODS

Isoenzymes and polymerase chain reaction (PCR) targeting ITSrDNA region followed by sequencing were conducted for typing the isolated parasite. A search for Leishmania virus infection was also performed.

FINDINGS

The mare presented skin nodules and ulcers in the left pinna caused by Leishmania spp. that was detected by culture and PCR. The parasite was identified as Leishmania (Mundinia) martiniquensis, infected by Leishbunyavirus (LBV), representing the first description of this species in South America. The animal travelled to different Brazilian regions, but not to outside the country.

MAIN CONCLUSIONS

The worldwide distribution of L. martiniquensis and its infection by LBV were confirmed in this study, indicating the autochthonous transmission cycle in Brazil. The clinical profile of the disease in the mare, showing fast spontaneous healing of cutaneous lesions, may indicate that skin lesions related to L. martiniquensis infection in horses might be underdiagnosed.

Transmission Risk Prediction and Evaluation of Mountain-Type Zoonotic Visceral Leishmaniasis in China Based on Climatic and Environmental Variables

With global warming and socioeconomic developments, there is a tendency toward the emergence and spread of mountain-type zoonotic visceral leishmaniasis (MT-ZVL) in China. Timely identification of the transmission risk and spread of MT-ZVL is, therefore, of great significance for effectively interrupting the spread of MT-ZVL and eliminating the disease. In this study, 26 environmental variables—namely, climatic, geographical, and 2 socioeconomic indicators were collected from regions where MT-ZVL patients were detected during the period from 2019 to 2021, to create 10 ecological niche models. The performance of these ecological niche models was evaluated using the area under the receiver-operating characteristic curve (AUC) and true skill statistic (TSS), and ensemble models were created to predict the transmission risk of MT-ZVL in China. All ten ecological niche models were effective at predicting the transmission risk of MT-ZVL in China, and there were significant differences in the mean AUC (H = 33.311, p < 0.05) and TSS values among these ten models (H = 26.344, p < 0.05). The random forest, maximum entropy, generalized boosted, and multivariate adaptive regression splines showed high performance at predicting the transmission risk of MT-ZVL (AUC > 0.95, TSS > 0.85). Ensemble models predicted a transmission risk of MT-ZVL in the provinces of Shanxi, Shaanxi, Henan, Gansu, Sichuan, and Hebei, which was centered in Shanxi Province and presented high spatial clustering characteristics. Multiple ensemble ecological niche models created based on climatic and environmental variables are effective at predicting the transmission risk of MT-ZVL in China. This risk is centered in Shanxi Province and tends towards gradual radiation dispersion to surrounding regions. Our results provide insights into MT-ZVL surveillance in regions at high risk of MT-ZVL.

Robust comparative performance of genomic DNA extraction methods from non-engorged phlebotomine sandflies

The present study is a comparative analysis of DNeasy Blood & Tissue Qiagen® kit (Qiagen®, Hilden, Alemanha), salting out, HotShot and phenol-chloroform protocols to extract DNA from sandflies. In addition, a comparative test using sandflies with and without eyes evaluated the potential inhibitory effect in the cPCR. An inhibition test was performed using an exogenous DNA added to the qPCR. The genomic DNA quality of each sample was evaluated by cPCR based on the cytochrome c oxidase subunit I (cox1) gene. The DNA extraction protocols showed the following percentage of amplification: HotShot (91.6% [55/60]), salting out (71.6% [43/60]), phenol-chloroform (95% [57/60]) and kit DNeasy Blood & Tissue Qiagen® (73.3% [44/60]). The phenol-chloroform method achieved a significantly higher frequency of cox1 gene amplification. The pigment present in the phlebotomine's eyes seems to inhibit cPCR reactions since the frequency of amplification of the cox1 gene increased in the sandflies without eyes (p < 0.0001). The HotShot method showed the highest inhibitory potential. These manual extraction techniques can be an inexpensive and effective alternative to study vector-pathogen interactions.

Ecological characterization of a cutaneous leishmaniasis outbreak through remotely sensed land cover changes

In this work we assessed the environmental factors associated with the spatial distribution of a cutaneous leishmaniasis (CL) outbreak during 2015-2016 in north-eastern Argentina to understand its typical or atypical eco-epidemiological pattern. We combined locations of human CL cases with relevant predictors derived from analysis of remote sensing imagery in the framework of ecological niche modelling and trained MaxEnt models with cross-validation for predictors estimated at different buffer areas relevant to CL vectors (50 and 250 m radii). To account for the timing of biological phenomena, we considered environmental changes occurring in two periods, 2014-2015 and 2015-2016. The remote sensing analysis identified land cover changes in the surroundings of CL cases, mostly related to new urbanization and flooding. The distance to such changes was the most important variable in most models. The weighted average map denoted higher suitability for CL in the outskirts of the city of Corrientes and in areas close to environmental changes. Our results point to a scenario consistent with a typical CL outbreak, i.e. changes in land use or land cover are the main triggering factor and most affected people live or work in border habitats.

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.

Fifty years of struggle to control cutaneous leishmaniasis in the highest endemic county in Iran: A longitudinal observation inferred with interrupted time series model

Negligible data are available following major social activities and environmental changes on leishmaniasis. Therefore, how interactions between these events influence cutaneous leishmaniasis (CL) risk is not well-known. This longitudinal study was undertaken to explore the impact of interventions conducted between 1971 and 2020 in Bam county, which has had the highest disease burden in Iran. Only confirmed CL cases during this period were taken into account. Data were analyzed by SPSS 22 using the X² test to assess the significance of the difference between proportions. Moreover, we used interrupted time series (ITS) to assess the impact of three environmental events during this period. Overall, 40,164 cases of CL occurred in the past five decades. Multiple complex factors were among the leading causes that synergistically induced the emergence/re-emergence of CL outbreaks in Bam. The main factors attributed negatively to CL control were cessation of malaria spraying activity, expansion of the city spaces, and a massive earthquake creating new breeding potentials for the vectors. The highest impact on CL incidence during these years was related to the earthquake [coefficient = 17.8 (95% CI: 11.3, 22.7); p-value < 0.001]. Many factors can contribute to CL outbreaks in endemic foci. They also can cause new foci in new areas. Since humans are the single reservoir for CL in this area, early detection and effective management significantly contribute to controlling CL to reduce the disease burden. However, essential evidence gaps remain, and new tools are crucial before the disease can ultimately be controlled. Nevertheless, sustained funding and more trained task forces are essential to strengthen surveillance and case management and monitor the interventions’ impact.

We aimed to conduct this longitudinal observation to assess the impact of interventions applied between 1971 and 2020 in Bam county, Iran’s highest anthroponotic cutaneous leishmaniasis burden. Only confirmed CL cases were taken into account. Overall, 40,164 cases of CL occurred in the past five decades. Multiple complex factors were among the leading causes that synergistically induced the emergence/re-emergence of CL outbreaks in Bam. The main factors attributed negatively to CL control were cessation of malaria spraying activity, expansion of the city spaces, and a massive earthquake creating new breeding potentials for the vectors. Since humans are the single reservoir host for CL in this area, early detection and effective management significantly contribute to controlling CL to reduce the disease burden. However, continuous funding and more trained forces are critical to strengthening surveillance and case management and monitoring the interventions’ impact.

Ecological niche modeling predicting the potential distribution of African horse sickness virus from 2020 to 2060

African horse sickness is a vector-borne, non-contagious and highly infectious disease of equines caused by African horse sickness viruses (AHSv) that mainly affect horses. The occurrence of the disease causes huge economic impacts because of its high fatality rate, trade ban and disease control costs. In the planning of vectors and vector-borne diseases like AHS, the application of Ecological niche models (ENM) used an enormous contribution in precisely delineating the suitable habitats of the vector. We developed an ENM to delineate the global suitability of AHSv based on retrospective outbreak data records from 2005 to 2019. The model was developed in an R software program using the Biomod2 package with an Ensemble modeling technique. Predictive environmental variables like mean diurnal range, mean precipitation of driest month(mm), precipitation seasonality (cv), mean annual maximum temperature (^oc), mean annual minimum temperature (^oc), mean precipitation of warmest quarter(mm), mean precipitation of coldest quarter (mm), mean annual precipitation (mm), solar radiation (kj /day), elevation/altitude (m), wind speed (m/s) were used to develop the model. From these variables, solar radiation, mean maximum temperature, average annual precipitation, altitude and precipitation seasonality contributed 36.83%, 17.1%, 14.34%, 7.61%, and 6.4%, respectively. The model depicted the sub-Sahara African continent as the most suitable area for the virus. Mainly Senegal, Burkina Faso, Niger, Nigeria, Ethiopia, Sudan, Somalia, South Africa, Zimbabwe, Madagascar and Malawi are African countries identified as highly suitable countries for the virus. Besides, OIE-listed disease-free countries like India, Australia, Brazil, Paraguay and Bolivia have been found suitable for the virus. This model can be used as an epidemiological tool in planning control and surveillance of diseases nationally or internationally.

Biodiversity and vector-borne diseases: host dilution and vector amplification occur simultaneously for Amazonian leishmaniases

Changes in biodiversity may impact infectious disease transmission through multiple mechanisms. We explored the impact of biodiversity changes on the transmission of Amazonian leishmaniases, a group of wild zoonoses transmitted by phlebotomine sand flies (Psychodidae), which represent an important health burden in a region where biodiversity is both rich and threatened. Using molecular analyses of sand fly pools and blood-fed dipterans, we characterized the disease system in forest sites in French Guiana undergoing different levels of human-induced disturbance. We show that the prevalence of Leishmania parasites in sand flies correlates positively with the relative abundance of mammal species known as Leishmania reservoirs. In addition, Leishmania reservoirs tend to dominate in less diverse mammal communities, in accordance with the dilution effect hypothesis. This results in a negative relationship between Leishmania prevalence and mammal diversity. On the other hand, higher mammal diversity is associated with higher sand fly density, possibly because more diverse mammal communities harbor higher biomass and more abundant feeding resources for sand flies, although more research is needed to identify the factors that shape sand fly communities. As a consequence of these antagonistic effects, decreased mammal diversity comes with an increase of parasite prevalence in sand flies, but has no detectable impact on the density of infected sand flies. These results represent additional evidence that biodiversity changes may simultaneously dilute and amplify vector-borne disease transmission through different mechanisms that need to be better understood before drawing generalities on the biodiversity-disease relationship.

Integration of phlebotomine ecological niche modelling, and mapping of cutaneous leishmaniasis surveillance data, to identify areas at risk of under-estimation

INTRODUCTION

Passive surveillance systems are thought to under-estimate the true incidence of American cutaneous leishmaniasis (ACL) by two- to five-fold. Ecological niche models based on remotely sensed data can identify environmental factors which favor phlebotomine vectors. Here we report an integrated approach to identifying areas at risk of cutaneous leishmaniasis by applying spatial analysis methods to niche model results, and local surveillance data, in two locations in Colombia with differing vector ecology. The objective was to identify townships in which later phases of the project could implement community-based surveillance to obtain direct estimates of under-reporting.

MATERIALS AND METHODS

The study was carried out in one municipality in each of two departments of the Andean region of Colombia: Pueblo Rico in Risaralda, and Rovira in Tolima. Niche mapping by maximum entropy, based on published and unpublished existing locations of Pintomyia (Pifanomyia) longiflocosa and Psychodopygus panamensis, and using variables on land cover, climate and elevation. Field catches were done in each municipality to test predictions of high relative probability of presence. The niche model results were included as a predictor in a conditional autoregressive spatial model, in which the outcome variable was the number of cases by township, as detected by passive surveillance.

RESULTS

Having rarefied 173 geolocated records, 46 of Pi. longiflocosa and 57 of Ps. panamensis were used for the niche modelling. At the national level, both species had high relative probability of presence on parts of the slopes of the three Andean cordilleras. Pi. longiflocosa also has a high relative probability of presence in the higher parts of the Magdalena valley, as does Ps. panamensis in some areas close to the Caribbean coast. At the local level, field catches confirmed that Pi. longiflocosa was the most abundant species in Rovira, and likewise Ps. panamensis in Pueblo Rico. The spatial regression showed that the incidence of ACL, according to surveillance, was positively, but not statistically significantly, associated with the relative probability of presence from the risk model.

CONCLUSIONS

These niche maps bring together published and unpublished results on phlebotomine species which are important vectors in Colombia. Maps of the fitted values of incidence were used to guide the selection of townships in which further phases of the study will attempt to quantify the extent of under-estimation of ACL incidence.

Outbreak of Cutaneous Leishmaniasis among military personnel in French Guiana, 2020: Clinical, phylogenetic, individual and environmental aspects

Background

Cutaneous Leishmaniasis (CL) is endemic in French Guiana but cases are usually sporadic. An outbreak signal was issued on May 15^th 2020 with 15 suspected cases after a military training course in the rainforest. An outbreak investigation was carried out.

Methodology/Principal findings

Thirty cases were confirmed. Leishmania guyanensis was the most frequent species (90%). The most frequent presentation was ulcerative (90%). Lesions on the face and hands were frequent (40% each). Eight cases (26%) presented a poor outcome after treatment with pentamidine and required a second line with amphotericin B. Three of them required further treatments with meglumine antimoniate or miltefosine. Two spots within the training area were deemed as likely sites of contamination, due to illegal logging. The isolated Leishmania strains did not form a separate cluster. Participation in Week 13 of year 2020 was associated with infection (OR = 4.59 [1.10–19.83]; p = 0.016) while undergoing only the “Fighting” exercise was protective (OR = 0.1 [0–0.74]; p = 0.021). There was no association between infection and other risk factors at the individual level. The attack rate of Regiment B (14/105 = 13.3%) was significantly higher (OR = 4.22 [1.84–9.53], p = 0.0001) compared to Regiment A (16/507 = 3.2%). The attack rate during this training course (30/858 = 3.5%) was significantly higher (OR 2.29 [1.28–4.13]; p = 0.002) than for other missions in French Guiana during the same period (22/1427 = 1.5%).

Conclusions

This outbreak could be explained by a combination of factors: climatic conditions around week 13, at-risk activities including night trainings, absence of impregnation, a lesser experience of rainforest duties in Regiment B and illegal logging attracting sandflies on military training grounds.

Cutaneous Leishmaniasis is caused by parasites of the Leishmania genus and infects humans after a sandfly bite. Outbreaks are rare and hard to investigate in isolated tropical areas. In this study, the authors explored the different possible origins of an outbreak of cutaneous leishmaniasis among soldiers training in the rainforest of French Guiana. The outbreak occurred in March 2020. Concerning the symptoms, several patients presented resistant infections and multiple lines of treatment, raising the issue of resistant Leishmania strains. The different strains isolated during the outbreak were not genetically closed, as far as routine PCR techniques would indicate. The authors looked for individual behaviours exposing soldiers to sandfly bites but none was significantly associated with infection. The authors found two spots in the military training areas where illegal logging probably increased the density of sandflies and put service members at risk. The 13^th week of 2020 was associated to a higher risk of infection due to climatic conditions. This study shows how interactions between humans and the rainforest can increase the risk of parasitic outbreaks.

Interaction between environmental and socioeconomic determinants for cutaneous leishmaniasis risk in Latin America

OBJECTIVE

Determine and characterize potential risk areas for the occurrence of cutaneous leishmaniasis (CL) in Latin America (LA).

METHOD

Ecological observational study with observation units defined by municipalities with CL transmission between 2014-2018. Environmental and socioeconomic variables available for at least 85% of the municipalities were used, combined in a single database, utilizing the R software. The principal component analysis methodology was combined with a hierarchical cluster analysis to group clusters of municipalities based on their similarity. The V-test was estimated to define the positive or negative association of the variables with the clusters and separation by natural breaks was used to determine which ones contributed the most to each cluster. Information on cases was also incorporated in the analyses to attribute CL risk for each cluster.

RESULTS

This study included 4,951 municipalities with CL transmission (36.5% of the total in LA) and seven clusters were defined by their association with 18 environmental and socioeconomic variables. The historical risk of CL is positively associated with the Amazonian, Andean and Savannah clusters in a decreasingly manner; and negatively associated with the Forest evergreen, Forest/crop and Forest/populated clusters. The Agricultural cluster did not reveal any association with the CL cases.

CONCLUSIONS

The study made it possible to identify and characterize the CL risk by clusters of municipalities and to recognize the epidemiological distribution pattern of transmission, which provides managers with better information for intersectoral interventions to control CL.

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.

Infestation risk of the intermediate snail host of Schistosoma japonicum in the Yangtze River Basin: improved results by spatial reassessment and a random forest approach

BACKGROUND

Oncomelania hupensis is only intermediate snail host of Schistosoma japonicum, and distribution of O. hupensis is an important indicator for the surveillance of schistosomiasis. This study explored the feasibility of a random forest algorithm weighted by spatial distance for risk prediction of schistosomiasis distribution in the Yangtze River Basin in China, with the aim to produce an improved precision reference for the national schistosomiasis control programme by reducing the number of snail survey sites without losing predictive accuracy.

METHODS

The snail presence and absence records were collected from Anhui, Hunan, Hubei, Jiangxi and Jiangsu provinces in 2018. A machine learning of random forest algorithm based on a set of environmental and climatic variables was developed to predict the breeding sites of the O. hupensis intermediated snail host of S. japonicum. Different spatial sizes of a hexagonal grid system were compared to estimate the need for required snail sampling sites. The predictive accuracy related to geographic distances between snail sampling sites was estimated by calculating Kappa and the area under the curve (AUC).

RESULTS

The highest accuracy (AUC = 0.889 and Kappa = 0.618) was achieved at the 5 km distance weight. The five factors with the strongest correlation to O. hupensis infestation probability were: (1) distance to lake (48.9%), (2) distance to river (36.6%), (3) isothermality (29.5%), (4) mean daily difference in temperature (28.1%), and (5) altitude (26.0%). The risk map showed that areas characterized by snail infestation were mainly located along the Yangtze River, with the highest probability in the dividing, slow-flowing river arms in the middle and lower reaches of the Yangtze River in Anhui, followed by areas near the shores of China's two main lakes, the Dongting Lake in Hunan and Hubei and the Poyang Lake in Jiangxi.

CONCLUSIONS

Applying the machine learning of random forest algorithm made it feasible to precisely predict snail infestation probability, an approach that could improve the sensitivity of the Chinese schistosome surveillance system. Redesign of the snail surveillance system by spatial bias correction of O. hupensis infestation in the Yangtze River Basin to reduce the number of sites required to investigate from 2369 to 1747.

Ecology, evolution, and epidemiology of zoonotic and vector-borne infectious diseases in French Guiana: Transdisciplinarity does matter to tackle new emerging threats

French Guiana is a European ultraperipheric region located on the northern Atlantic coast of South America. It constitutes an important forested region for biological conservation in the Neotropics. Although very sparsely populated, with its inhabitants mainly concentrated on the Atlantic coastal strip and along the two main rivers, it is marked by the presence and development of old and new epidemic disease outbreaks, both research and health priorities. In this review paper, we synthetize 15 years of multidisciplinary and integrative research at the interface between wildlife, ecosystem modification, human activities and sociodemographic development, and human health. This study reveals a complex epidemiological landscape marked by important transitional changes, facilitated by increased interconnections between wildlife, land-use change and human occupation and activity, human and trade transportation, demography with substantial immigration, and identified vector and parasite pharmacological resistance. Among other French Guianese characteristics, we demonstrate herein the existence of more complex multi-host disease life cycles than previously described for several disease systems in Central and South America, which clearly indicates that today the greater promiscuity between wildlife and humans due to demographic and economic pressures may offer novel settings for microbes and their hosts to circulate and spread. French Guiana is a microcosm that crystallizes all the current global environmental, demographic and socioeconomic change conditions, which may favor the development of ancient and future infectious diseases.

[Interaction among environmental and socioeconomic determinants of risk for cutaneous leishmaniasis in Latin AmericaInteração entre os determinantes ambientais e socioeconômicos para o risco de leishmaniose cutânea na América Latina]

OBJECTIVE

Determine and characterize areas at potential risk for the occurrence of cutaneous leishmaniasis (CL) in Latin America.

METHOD

Ecological observational study with observation units defined by municipalities with CL transmission during 2014-2018. Environmental and socioeconomic variables available for at least 85% of municipalities were combined in a single database, using R software. Principal component analysis was combined with hierarchical cluster analysis for the formation of clusters of municipalities according to their similarity. The V-test was used to define positive or negative association of variables with clusters and separation by natural divisions to determine which contributed more to each cluster. Cases were included to attribute CL risk for each cluster.

RESULTS

The study included 4 951 municipalities with CL transmission (36.5% of municipalities in Latin America); seven clusters were defined by their association with 18 environmental and socioeconomic variables. Historical risk of CL is associated positively and in descending order with the Amazonian, Andean, and Savanna clusters; and negatively with the Forest/perennial, Forest/cultivated, and Forest/populated clusters. The Agricultural cluster showed no association with CL cases.

CONCLUSIONS

The study made it possible to identify and characterize CL risk by clusters of municipalities and to understand the characteristic epidemiological distribution patterns of transmission, providing program managers with better information for intersectoral interventions to control CL.

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.

Geographic abundance patterns explained by niche centrality hypothesis in two Chagas disease vectors in Latin America

Ecoepidemiological scenarios for Chagas disease transmission are complex, so vector control measures to decrease human–vector contact and prevent infection transmission are difficult to implement in all geographic contexts. This study assessed the geographic abundance patterns of two vector species of Chagas disease: Triatoma maculata (Erichson, 1848) and Rhodnius pallescens (Barber, 1932) in Latin America. We modeled their potential distribution using the maximum entropy algorithm implemented in Maxent and calculated distances to their niche centroid by fitting a minimum-volume ellipsoid. In addition, to determine which method would accurately explain geographic abundance patterns, we compared the correlation between population abundance and the distance to the ecological niche centroid (DNC) and between population abundance and Maxent environmental suitability. The potential distribution estimated for T. maculata showed that environmental suitability covers a large area, from Panama to Northern Brazil. R. pallescens showed a more restricted potential distribution, with environmental suitability covering mostly the coastal zone of Costa Rica and some areas in Nicaragua, Honduras, Belize and the Yucatán Peninsula in Mexico, northern Colombia, Acre, and Rondônia states in Brazil, as well as a small region of the western Brazilian Amazon. We found a negative slope in the relationship between population abundance and the DNC in both species. R. pallecens has a more extensive potential latitudinal range than previously reported, and the distribution model for T. maculata corroborates previous studies. In addition, population abundance increases according to the niche centroid proximity, indicating that population abundance is limited by the set of scenopoetic variables at coarser scales (non-interactive variables) used to determine the ecological niche. These findings might be used by public health agencies in Latin America to implement actions and support programs for disease prevention and vector control, identifying areas in which to expand entomological surveillance and maintain chemical control, in order to decrease human–vector contact.

Spatial epidemiology of yellow fever: Identification of determinants of the 2016-2018 epidemics and at-risk areas in Brazil

Optimise control strategies of infectious diseases, identify factors that favour the circulation of pathogens, and propose risk maps are crucial challenges for global health. Ecological niche modelling, once relying on an adequate framework and environmental descriptors can be a helpful tool for such purposes. Despite the existence of a vaccine, yellow fever (YF) is still a public health issue. Brazil faced massive sylvatic YF outbreaks from the end of 2016 up to mid-2018, but cases in human and non-human primates have been recorded until the beginning of 2020. Here we used both human and monkey confirmed YF cases from two epidemic periods (2016/2017 and 2017/2018) to describe the spatial distribution of the cases and explore how biotic and abiotic factors drive their occurrence. The distribution of YF cases largely overlaps for humans and monkeys, and a contraction of the spatial extent associated with a southward displacement is observed during the second period of the epidemics. More contributive variables to the spatiotemporal heterogeneity of cases were related to biotic factors (mammal richness), abiotic factors (temperature and precipitation), and some human-related variables (population density, human footprint, and human vaccination coverage). Both projections of the most favourable conditions showed similar trends with a contraction of the more at-risk areas. Once extrapolated at a large scale, the Amazon basin remains at lower risk, although surrounding forest regions and notably the North-West region, would face a higher risk. Spatial projections of infectious diseases often relied on climatic variables only; here for both models, we instead highlighted the importance of considering local biotic conditions, hosts vulnerability, social and epidemiological factors to run the spatial risk analysis correctly: all YF cases occurring later on, in 2019 and 2020, were observed in the predicted at-risk areas.

The environmental drivers of bacterial meningitis epidemics in the Democratic Republic of Congo, central Africa

INTRODUCTION

Bacterial meningitis still constitutes an important threat in Africa. In the meningitis belt, a clear seasonal pattern in the incidence of meningococcal disease during the dry season has been previously correlated with several environmental parameters like dust and sand particles as well as the Harmattan winds. In parallel, the evidence of seasonality in meningitis dynamics and its environmental variables remain poorly studied outside the meningitis belt. This study explores several environmental factors associated with meningitis cases in the Democratic Republic of Congo (DRC), central Africa, outside the meningitis belt area.

METHODS

Non-parametric Kruskal-Wallis' tests were used to establish the difference between the different health zones, climate and vegetation types in relation to both the number of cases and attack rates for the period 2000-2018. The relationships between the number of meningitis cases for the different health zones and environmental and socio-economical parameters collected were modeled using different generalized linear (GLMs) and generalized linear mixed models (GLMMs), and different error structure in the different models, i.e., Poisson, binomial negative, zero-inflated binomial negative and more elaborated multi-hierarchical zero-inflated binomial negative models, with randomization of certain parameters or factors (health zones, vegetation and climate types). Comparing the different statistical models, the model with the smallest Akaike's information criterion (AIC) were selected as the best ones. 515 different health zones from 26 distinct provinces were considered for the construction of the different GLM and GLMM models.

RESULTS

Non-parametric bivariate statistics showed that there were more meningitis cases in urban health zones than in rural conditions (χ2 = 6.910, p-value = 0.009), in areas dominated by savannah landscape than in areas with dense forest or forest in mountainous areas (χ2 = 15.185, p-value = 0.001), and with no significant difference between climate types (χ2 = 1.211, p-value = 0,449). Additionally, no significant difference was observed for attack rate between the two types of heath zones (χ2 = 0.982, p-value = 0.322). Conversely, strong differences in attack rate values were obtained for vegetation types (χ2 = 13.627, p-value = 0,001) and climate types (χ2 = 13.627, p-value = 0,001). This work demonstrates that, all other parameters kept constant, an urban health zone located at high latitude and longitude eastwards, located at low-altitude like in valley ecosystems predominantly covered by savannah biome, with a humid tropical climate are at higher risk for the development of meningitis. In addition, the regions with mean range temperature and a population with a low index of economic well-being (IEW) constitute the perfect conditions for the development of meningitis in DRC.

CONCLUSION

In a context of global environmental change, particularly climate change, our findings tend to show that an interplay of different environmental and socio-economic drivers are important to consider in the epidemiology of bacterial meningitis epidemics in DRC. This information is important to help improving meningitis control strategies in a large country located outside of the so-called meningitis belt.

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.