Estimating the optimal interval between rounds of indoor residual spraying of insecticide using malaria incidence data from cohort studies

Abstract

Background Indoor residual spraying (IRS) reduces vector densities and malaria transmission, however, the most effective spraying intervals for IRS have not been well established. We estimated the optimal timing interval for IRS using a statistical approach. Methods Six rounds of IRS were implemented in Tororo District, a historically high malaria transmission setting in Uganda, during the study period (3 rounds with bendiocarb active ingredient (Ficam®): December 2014 to December 2015, and 3 rounds with pirimiphos methyl active ingredient (Actellic 300®CS): June 2016 to July 2018). A generalized additive model was used to estimate the optimal timing interval for IRS based on the predicted malaria incidence. The model was fitted to clinical incidence data from a cohort of children aged 0.5–10 years from selected households observed throughout the study period. Results 494 children, 67% aged less than 5 years at enrolment were analysed. Six-months period incidence of malaria decreased from 2.96 per person-years at the baseline to 1.74 following the first round of IRS and then to 0.02 after 6 rounds of IRS. The optimal time interval for IRS differed between bendiocarb and pirimiphos methyl and by IRS round. To retain an optimum impact, bendiocarb would require respraying 17 (95% CI: 14.2–21.0) weeks after application whereas pirimiphos methyl could remain impactful for 40 (95% CI: 37.0–42.8) weeks, although in the final year this estimates 36 (95% CI: 32.7–37.7) weeks. However, we could not estimate from the data the optimal time after the second and third rounds of bendiocarb and after the second round of pirimiphos methyl. Neither the amount of rainfall nor the EIR nor the distribution of nets were found to be statistically significant for determining the time period between spray rounds. Conclusion In our setting, the effect of the two IRS products was distinct. Statistically, pirimiphos methyl provided a longer window of protection than bendiocarb, although impact varied between different spray rounds and years which was not explained by rainfall or EIR or distribution of nets in our statistical approach. Understanding the effectiveness of IRS and how long it lasts can help for planning campaigns, but one should consider the financial cost and insecticide resistance. Monitoring the timing of spray campaigns using clinical incidence could be repeated in future programs to help determine the average period of protectivity of these products.

Standardised bioassays reveal that mosquitoes learn to avoid compounds used in chemical vector control after a single sub-lethal exposure

“…Pesticide sub-lethality is also inherent to various scenarios of bed net aging, deterioration and missuses which are compounded by infrequent replacement [44][45][46][47] . The same applies to IRS and space spraying interventions which may again target resistant mosquito populations or be conducted at intervals that create many opportunities for sub-lethal exposures 48,49 .…”

East Africa International Center of Excellence for Malaria Research: Impact on Malaria Policy in Uganda

“… 13 , 14 These data informed the response to malaria resurgences after IRS withdrawal and provided information on appropriate IRS coverage, intervals, insecticides, and discontinuation strategies. 15 Most recently, we used MRC data to evaluate the impact of the COVID-19 epidemic on routine malaria indicators in Uganda from March 2020 to June 2021. We identified a reduction in the proportion of suspected malaria cases tested by rapid diagnostic tests, but COVID-19 did not otherwise appear to significantly impact routine malaria indicators in rural Uganda.…”

Modelling longitudinal binary outcomes with outcome dependent observation times: an application to a malaria cohort study

“…The data were collected as part of the Program for Resistance, Immunology, Surveillance and Modelling of malaria (PRISM) study [ 4 ]. More specifically, the PRISM data considered in this paper belongs to Phase I of the project conducted between August 2011 and September 2017 [ 4 , 16 ]. The aforementioned study regions were characterized by distinct transmission intensities, with the highest intensity reported in Nagongera, followed by Kihihi and with Walukuba having the smallest intensity [ 4 , 5 ], at least in Phase 1 of the study.…”