ArticlePLoS neglected tropical diseases2017
Modeling zoonotic cutaneous leishmaniasis incidence in central Tunisia from 2009-2015: Forecasting models using climate variables as predictors.
Article in PLoS neglected tropical diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.
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Who cites it
34 citing papers in PubMed, 1 synthesis or guideline pooled it, 75 citations in OpenAlex.
- Environmental and socioeconomic risk factors associated with visceral and cutaneous leishmaniasis: a systematic review.Parasitology research · 2020Pooled it
- The pitfalls of incidence-based time series regression for inferring the effects of weather on infectious diseases.PLoS computational biology · 2026Article
- Coupled Atlantic atmosphere-ocean variability modulates cutaneous leishmaniasis in North Africa, enabling long-lead seasonal forecasts.Science advances · 2026Article
- Spatiotemporal dynamics of the capture rate of Rattus tanezumi and its implications for rodent-borne diseases in the Three Gorges Reservoir Area, China.Environmental monitoring and assessment · 2026Article
- Epidemiological study of cutaneous leishmaniasis in Algeria.Open veterinary journal · 2026Article
- The impact of El Niño-Southern Oscillation on the incidence of infectious diarrhea in China: insights from a 15-year national surveillance analysis.Frontiers in public health · 2026Article
- Effect of flood on the cutaneous leishmaniasis incidence in northeast of Iran: an interrupted time series study.BMC infectious diseases · 2025Article
- A Comprehensive Review of Epidemiology, Environmental Factors, and Control Strategies for Zoonotic CutaneousAdvanced biomedical research · 2025Review
- Clinical polymorphism of zoonotic cutaneous leishmaniasis: combination of the clinical and the parasitological diagnosis.Parasitology research · 2024Article
- The Impact of Climatological Factors on the Incidence of Cutaneous Leishmaniasis (CL) in Colombian Municipalities from 2017 to 2019.Pathogens (Basel, Switzerland) · 2024Article
- Non-linear effects of meteorological factors on COVID-19: An analysis of 440 counties in the americas.Heliyon · 2024Article
- A proposed One Health approach to control yellow fever outbreaks in Uganda.One health outlook · 2024Review
- Seasonal Patterns of Zoonotic Cutaneous Leishmaniasis Caused by L. major and Transmitted by Phlebotomus papatasi in the North Africa Region, a Systematic Review and a Meta-AnalysisMicroorganisms · 2022Article
- Article
- Environmental, Climatic, and Parasite Molecular Factors Impacting the Incidence of Cutaneous Leishmaniasis Due toMicroorganisms · 2022Article
- A Review on Climate, Air Pollution, and Health in North Africa.Current environmental health reports · 2022Review
- Geographic distribution ofParasite epidemiology and control · 2022Article
- Determination of the trend of incidence of cutaneous leishmaniasis in Kerman province 2014-2020 and forecasting until 2023. A time series study.PLoS neglected tropical diseases · 2022Article
- Taxonomy for citizen actions on public health and climate change: a proposal.Revista de saude publica · 2022Article
- The effect and prediction of diurnal temperature range in high altitude area on outpatient and emergency room admissions for cardiovascular diseases.International archives of occupational and environmental health · 2021Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Transmission of zoonotic cutaneous leishmaniasis (ZCL) depends on the presence, density and distribution of Leishmania major rodent reservoir and the development of these rodents is known to have a significant dependence on environmental and climate factors. ZCL in Tunisia is one of the most common forms of leishmaniasis. The aim of this paper was to build a regression model of ZCL cases to identify the relationship between ZCL occurrence and possible risk factors, and to develop a predicting model for ZCL's control and prevention purposes. Monthly reported ZCL cases, environmental and bioclimatic data were collected over 6 years (2009-2015). Three rural areas in the governorate of Sidi Bouzid were selected as the study area. Cross-correlation analysis was used to identify the relevant lagged effects of possible risk factors, associated with ZCL cases. Non-parametric modeling techniques known as generalized additive model (GAM) and generalized additive mixed models (GAMM) were applied in this work. These techniques have the ability to approximate the relationship between the predictors (inputs) and the response variable (output), and express the relationship mathematically. The goodness-of-fit of the constructed model was determined by Generalized cross-validation (GCV) score and residual test. There were a total of 1019 notified ZCL cases from July 2009 to June 2015. The results showed seasonal distribution of reported ZCL cases from August to January. The model highlighted that rodent density, average temperature, cumulative rainfall and average relative humidity, with different time lags, all play role in sustaining and increasing the ZCL incidence. The GAMM model could be applied to predict the occurrence of ZCL in central Tunisia and could help for the establishment of an early warning system to control and prevent ZCL in central Tunisia.
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