JMIR Publications

ABSTRACT

Background:

Malaria is a global pandemic resulting in approximately 228 million cases globally, and 3.5 % of these is in South-East Asian countries including Indonesia. Following the World Health Organization (WHO) initiative, Indonesia is in the process of achieving malaria-free zone status by 2030. However, the Eastern part of Indonesia, including the East Nusa Tenggara Province (ENTP), still suffers from a disproportionately higher rate of malaria.

Objective:

The purposes of this cross-sectional study are to: (1) Determine the awareness, knowledge, attitudes, and practices (KAP) towards various aspects of malaria among rural adults and their associated factors including socio-demographic factors and ethnicities; (2) Assess the gap between coverage, access, and use of long-lasting insecticide-treated bed nets (LLINs) among the households; (3) Estimate the prevalence of, and factors associated with, malaria in rural adults; and (4) Develop a risk prediction model of malaria.

Methods:

A multi-stage cluster sampling procedure with a systematic random sampling procedure at cluster level 4 had been applied to recruit 1503 adults aged 18 years or over from ENTP. Each participant partook in a face-to-face interview to assess their awareness and KAP of malaria, practices of sleeping under LLINs, and malaria history. Information on socio-demographic, environmental, and lifestyle factors was documented. The proportion of malaria KAP and their variations across different socio-demographic and ethnicities will be analysed using descriptive statistics and Chi-square tests. Coverage and access to LLINs will be evaluated based on the WHO recommendation. Malaria risk factors will be analysed using a logistic regression method. Multilevel logistic regression will be applied to estimate the risk score of malaria.

Results:

Of 1503 participants, 1495 (99% participation rate) rural adults from 49 villages in the ENTP were interviewed from October to December 2019. The study results are expected to publish in peer review journals.

Conclusions:

The best malaria risk prediction model will be developed by this study. We believe that the protocol paper has developed a methodology to provide new evidence to guide health policy in supporting the ENTP government’s expectation to achieve the malaria-free rating by 2030.