Community’s Knowledge, Attitude and Practice toward Leptospirosis and its Prevention and Control: A Systematic Review

Author:

Hassan Mohd RohaizatORCID,Mohd Nordin Nor RumaizahORCID,Hayati Firdaus,Safian Nazarudin,Agustar Hani Kartini,Bejo Siti Khairani,Dapari RahmatORCID,Rahim Syed Sharizman Syed AbdulORCID,Azhar Zahir IzuanORCID,Jeffree Mohammad Saffree

Abstract

BACKGROUND: Multiple studies have been conducted on the level of knowledge, attitude, and preventive practices (KAP) towards leptospirosis, descriptively, analytically pertaining to its relationship and also associated factors such as sociodemographic and economic factors. Over the years, different community settings and sampling frames were applied. AIM: The goal of this review is to identify available literature evidence on the community's knowledge, attitudes, and behaviours about leptospirosis, taking into account variations and similarities in techniques, tools, and data analysis. METHODS: A literature search was undertaken using the electronic databases PubMed, Scopus, Web of Science, and Ovid. Open access articles produced between 2011 and 2021 were analysed, with an emphasis on community's KAP. RESULTS: Eight articles met the inclusion benchmarks. The relationship between knowledge, attitude and preventive practices is not congruent. However, most studies showed that good knowledge is attributed to good attitude, but attitude does not necessarily contribute to good practice. Socio-demographic factors such as educational level, ethnicity, age, income and geographical location (distance to the river) have an influence on knowledge, attitude and practice. CONCLUSION: More KAP studies with standardised methodology and questionnaires regarding leptospirosis are required in order to formulate effective, sustainable and replicable health program interventions to prevent the community from leptospirosis infection and fatality. In the future, more qualitative studies should be done to further investigate and combine with quantitative studies to form prediction modelling.

Publisher

Scientific Foundation SPIROSKI

Subject

General Medicine

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