Indoor residual spraying uptake and its effect on malaria morbidity in Ngoma district, Eastern province of Rwanda, 2018-2021

Olivier Nsekuye,Samuel S. Malamba,Ziad El-Khatib,Jared Omolo, Jean-Louis N. Mangara, Dunia Munyakanage, Aline Uwimana,Angela Umutoni,Naomi W. Lucchi, Edson Rwagasore, Daniel Ntabanganyimana, Jean-Claude Niyoyita, Henri Desire Uwayo,Theoneste Ntakirutimana, Samuel Rwunganira

crossref(2024)

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摘要
Abstract Background Indoor residual spraying (IRS) was implemented in Rwanda among districts with high transmission of malaria, including Ngoma District, which received the first IRS (IRS-1) in March 2019 before the peak season, and the second IRS (IRS-2) campaign in August 2020, which targeted 89,331 structures. This study was conducted to assess factors associated with IRS uptake and the effect of IRS intervention on malaria morbidity in the Ngoma district, Eastern Province, Rwanda. Method A household survey using a multistage cluster sampling design was used to randomly select households. A well-structured questionnaire was administered to the head of household or the designated household in May 2021. A logistic regression model adjusted for the complex survey design and weighted to account for the sampling design was used to assess factors associated with IRS uptake. A secondary data analysis of malaria cases registered in the Rwanda Health Management Information System (RHMIS) from January 2015 to December 2022 in Ngoma district was used to determine the effect of IRS on malaria morbidity using interrupted time series analysis. Results Six hundred thirty-six households headed by self-employed (aOR = 0.07; 95% CI: 0.01–0.55) and unemployed (aOR = 0.18; 95% CI: 0.03–0.99) individuals were less likely to take up IRS than households headed by farmers. Households receiving information about the IRS via media (aOR = 0.01; 95% CI: 0.00-0.17) were less likely to use the IRS than were those receiving information via community health workers. From the RHMIS, 919,843 malaria cases were identified. In the interrupted time series analysis, the baseline number of adjusted malaria cases was approximately 16,920. The first intervention in March 2019 led to a significant reduction of approximately 14,380 patients (p < 0.001), while the second intervention in August 2020 led to a decrease of approximately 2,495 patients, although the difference was not statistically significant (p = 0.098). Conclusion This study underscores the ability of IRS to reduce malaria incidence in Ngoma District. The influence of socioeconomic factors and information sources on IRS uptake calls for targeted strategies, comprehensive IRS education, and an integrated malaria control approach, including bed net usage and other prevention and control interventions.
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