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Spatiotemporal and molecular epidemiology of cutaneous leishmaniasis in Libya.

ABSTRACT: BACKGROUND:Cutaneous leishmaniasis (CL) is a major public health problem in Libya. In this paper, we describe the eco-epidemiological parameters of CL during the armed conflict period from January 2011 till December 2012. Current spatiotemporal distributions of CL cases were explored and projected to the future using a correlative modelling approach. In addition the present results were compared with our previous data obtained for the time period 1995-2008. METHODOLOGY/PRINCIPAL FINDINGS:We investigated 312 CL patients who presented to the Dermatology Department at the Tripoli Central Hospital and came from 81 endemic areas distributed in 10 districts. The patients presented with typical localized lesions which appeared commonly on the face, arms and legs. Molecular identification of parasites by a PCR-RFLP approach targeting the ITS1 region of the rDNA was successful for 81 patients with two causative species identified: L. major and L. tropica comprised 59 (72.8%) and 22 (27.2%) cases, respectively. Around 77.3% of L. tropica CL and 57.7% of L. major CL caused single lesions. Five CL patients among our data set were seropositive for HIV. L. tropica was found mainly in three districts, Murqub (27.3%), Jabal al Gharbi (27.3%) and Misrata (13.7%) while L. major was found in two districts, in Jabal al Gharbi (61%) and Jafara (20.3%). Seasonal occurrence of CL cases showed that most cases (74.2%) admitted to the hospital between November and March, L. major cases from November till January (69.4%), and L. tropica cases mainly in January and February (41%). Two risk factors were identified for the two species; the presence of previously infected household members, and the presence of rodents and sandflies in patient's neighborhoods. Spatiotemporal projections using correlative distribution models based on current case data and climatic conditions showed that coastal regions have a higher level of risk due to more favourable conditions for the transmitting vectors. CONCLUSION:Future projection of CL until 2060 showed a trend of increasing incidence of CL in the north-western part of Libya, a spread along the coastal region and a possible emergence of new endemics in the north-eastern districts of Libya. These results should be considered for control programs to prevent the emergence of new endemic areas taking also into consideration changes in socio-economical factors such as migration, conflicts, urbanization, land use and access to health care.

SUBMITTER: Amro A

PROVIDER: S-EPMC5605087 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Spatiotemporal and molecular epidemiology of cutaneous leishmaniasis in Libya.

Amro Ahmad A Al-Dwibe Hamida H Gashout Aisha A Moskalenko Olga O Galafin Marlena M Hamarsheh Omar O Frohme Marcus M Jaeschke Anja A Schönian Gabriele G Kuhls Katrin K

PLoS neglected tropical diseases 20170907 9

<h4>Background</h4>Cutaneous leishmaniasis (CL) is a major public health problem in Libya. In this paper, we describe the eco-epidemiological parameters of CL during the armed conflict period from January 2011 till December 2012. Current spatiotemporal distributions of CL cases were explored and projected to the future using a correlative modelling approach. In addition the present results were compared with our previous data obtained for the time period 1995-2008.<h4>Methodology/principal findi ...[more]

PMID: 28880944

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Project description:Leishmaniasis is a major neglected tropical disease which contributes a huge economic burden on already meager economic resources. The World Health Organization (WHO) has estimated an annual incidence of 700,000--1,000,000 patients and about 20,000-30,000 deaths per year. Approximately 66,941 patients of cutaneous leishmaniasis are reported annually in the Americas. In recent years, Nicaragua has presented alarmingly high numbers of patients and elevated incidence rates. Unfortunately, there are no detailed spatial descriptions on the epidemiological situation of leishmaniasis in this country. The objective of this study is to present descriptive data about the epidemiology of leishmaniasis in Nicaragua in the context of the distribution of this neglected tropical disease (NTD) in the Americas. This paper also provides an epidemiological update on different forms of leishmaniasis found in the three administrative regions of Nicaragua and its municipalities. Health authorities from the Ministry of Health of Nicaragua (MINSA) provided the entomological and epidemiological information for the different forms of the disease from 2001 to 2018. Prevalence, incidence rates, clinical classification of disease, age groups, sex, and geographic distribution by municipality and department are described in this study. Approximately 90%-95% of the national patients corresponded to CL and 5-10% correspond to MCL. The disease is distributed in the three regions of the country, with a higher burden in the Departments of Jinotega, Matagalpa and Atlántico Norte. The municipalities with the highest proportion of patients were El Cuá (23.92%), Waslala (14.16), Santa Maria de Pantasma (9.62%), Rancho Grande (9.03%) and Siuna (7.67%). There is an expansion of spatial distribution of CL and MCL in the North Central and South Atlantic regions of the country. These results could inform interventional strategies to address the burden of leishmaniasis in Nicaragua, which would improve the likelihood of meeting the goals for the Leishmaniasis Plan of Action for the Americas.

Project description:BackgroundLeishmaniasis is a neglected tropical vector-borne disease, which is on the rise in Sri Lanka. Spatiotemporal and risk factor analyses are useful for understanding transmission dynamics, spatial clustering and predicting future disease distribution and trends to facilitate effective infection control.MethodsThe nationwide clinically confirmed cutaneous leishmaniasis and climatic data were collected from 2001 to 2019. Hierarchical clustering and spatiotemporal cross-correlation analysis were used to measure the region-wide and local (between neighboring districts) synchrony of transmission. A mixed spatiotemporal regression-autoregression model was built to study the effects of climatic, neighboring-district dispersal, and infection carryover variables on leishmaniasis dynamics and spatial distribution. Same model without climatic variables was used to predict the future distribution and trends of leishmaniasis cases in Sri Lanka.ResultsA total of 19,361 clinically confirmed leishmaniasis cases have been reported in Sri Lanka from 2001-2019. There were three phases identified: low-transmission phase (2001-2010), parasite population buildup phase (2011-2017), and outbreak phase (2018-2019). Spatially, the districts were divided into three groups based on similarity in temporal dynamics. The global mean correlation among district incidence dynamics was 0.30 (95% CI 0.25-0.35), and the localized mean correlation between neighboring districts was 0.58 (95% CI 0.42-0.73). Risk analysis for the seven districts with the highest incidence rates indicated that precipitation, neighboring-district effect, and infection carryover effect exhibited significant correlation with district-level incidence dynamics. Model-predicted incidence dynamics and case distribution matched well with observed results, except for the outbreak in 2018. The model-predicted 2020 case number is about 5,400 cases, with intensified transmission and expansion of high-transmission area. The predicted case number will be 9115 in 2022 and 19212 in 2025.ConclusionsThe drastic upsurge in leishmaniasis cases in Sri Lanka in the last few year was unprecedented and it was strongly linked to precipitation, high burden of localized infections and inter-district dispersal. Targeted interventions are urgently needed to arrest an uncontrollable disease spread.

Project description:BackgroundCutaneous leishmaniasis (CL) is a wide-reaching infection of major public health concern. Iran is one of the six most endemic countries in the world. This study aims to provide a spatiotemporal visualization of CL cases in Iran at the county level from 2011 to 2020, detecting high-risk zones, while also noting the movement of high-risk clusters.MethodsOn the basis of clinical observations and parasitological tests, data of 154,378 diagnosed patients were obtained from the Iran Ministry of Health and Medical Education. Utilizing spatial scan statistics, we investigated the disease's purely temporal, purely spatial, spatial variation in temporal trends and spatiotemporal patterns. At P = 0.05 level, the null hypothesis was rejected in every instance.ResultsIn general, the number of new CL cases decreased over the course of the 9-year research period. From 2011 to 2020, a regular seasonal pattern, with peaks in the fall and troughs in the spring, was found. The period of September-February of 2014-2015 was found to hold the highest risk in terms of CL incidence rate in the whole country [relative risk (RR) = 2.24, P < 0.001)]. In terms of location, six significant high-risk CL clusters covering 40.6% of the total area of the country were observed, with the RR ranging from 1.87 to 9.69. In addition, spatial variation in the temporal trend analysis found 11 clusters as potential high-risk areas that highlighted certain regions with an increasing tendency. Finally, five space-time clusters were found. The geographical displacement and spread of the disease followed a moving pattern over the 9-year study period affecting many regions of the country.ConclusionsOur study has revealed significant regional, temporal, and spatiotemporal patterns of CL distribution in Iran. Over the years, there have been multiple shifts in spatiotemporal clusters, encompassing many different parts of the country from 2011 to 2020. The results reveal the formation of clusters across counties that cover certain parts of provinces, indicating the importance of conducting spatiotemporal analyses at the county level for studies that encompass entire countries. Such analyses, at a finer geographical scale, such as county level, might provide more precise results than analyses at the scale of the province.

Dataset Information

Spatiotemporal and molecular epidemiology of cutaneous leishmaniasis in Libya.

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Spatiotemporal and molecular epidemiology of cutaneous leishmaniasis in Libya.

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