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ORIGINAL ARTICLE
Year : 2018  |  Volume : 7  |  Issue : 1  |  Page : 37-40

Seasonality of leptospirosis and its association with rainfall and humidity in Ratnagiri, Maharashtra


1 Medical Officer, District Tuberculosis Centre, Vazirabad, Nanded, India
2 Medical Officer, ADHS Leprosy, Ratnagiri, India
3 District Health Officer, Ratnagiri, Maharashtra, India
4 District Tuberculosis Officer, Ratnagiri, Maharashtra, India

Correspondence Address:
Dr. Shivshakti D Pawar
TB Centre, Vazirabad, Nanded - 431 601, Maharashtra
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijhas.IJHAS_35_16

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CONTEXT: Leptospirosis is the disease which has worldwide occurrence, but the incidence is more in tropical countries. Disease outbreaks depend on the climatic factors which allow better survival of bacteria. AIMS: The aim of the study was (1) to study the seasonal pattern of leptospirosis cases and with rainfall and relative humidity and (2) to forecast the leptospirosis cases' occurrence based on the model. SUBJECTS AND METHODS: Retrospective time series analysis was carried out of leptospirosis cases registered in Ratnagiri, Maharashtra, during January 2011 to December 2015. STATISTICAL ANALYSIS: Patterns of occurrence of monthly cases and patterns of monthly rainfall and relative humidity were studied using cross-correlation function, autocorrelation function, partial autocorrelation function, and simple seasonal model (selected by expert modeler) were applied using SPSS version 20. RESULTS: A significant seasonal pattern is noted in the leptospirosis cases' occurrence. Cross-correlation function shows a significant highest correlation 1 month lag between the occurrence of heavy rainfall and outbreak of cases. SPSS expert modeler used to forecast the cases and could predict the 80% variability. CONCLUSIONS: Seasonal pattern of cases of leptospirosis was observed along with the correlation of rainfall. This forecasted model could be used by health administrators effectively to arrange the adequate resources on time to manage the outbreaks.


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