Unmasking Asymptomatic Malaria: The Role of Acquired Immunity and Integrated Interventions in Sustained Transmission Control

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Abstract Malaria remains a significant global health challenge, with high morbidity and mortality. In endemic areas, repeated exposure improves partial immunity, leading to asymptomatic carriers with low parasitemia who act as hidden reservoirs, perpetuating transmission. This study develops a malaria transmission model with heterogeneous mosquito biting that integrates immunity dynamics to examine how repeated exposure influences immunity acquisition, transitions between symptomatic and asymptomatic states, and overall transmission patterns. Calibrated with annual confirmed case data from Kenya, the model is used to assess the effects of immunity dynamics, asymptomatic carriers, and insecticide-treated net (ITN) use or relaxation on malaria transmission, morbidity, mortality, and intervention efficacy across varying levels of immunity and exposure. Global sensitivity analysis and simulations of the model identify mosquito lifespan, recruitment rate, and infection probabilities as key transmission drivers, supporting integrated vector control and timely treatment to reduce cases and sustain population-level immunity. In particular, this study identifies adult mosquito mortality as the most influential factor in malaria transmission, highlighting the strong impact of interventions such as ITNs and indoor residual spraying (IRS). However, while these measures effectively reduce mosquito bites and transmission, they may inadvertently diminish clinical immunity, leaving individuals more vulnerable to severe disease upon future exposure. This concern is compounded by the presence of backward bifurcation, which indicates that reducing the basic reproduction number ($R_0$) below one may not be sufficient for elimination unless initial infection levels are also addressed. The study reveals that mosquito biting heterogeneity is a critical driver of immunity, disease dynamics, and altered intervention effectiveness--often misrepresented under uniform assumptions. Accurately capturing this variability is not just a modeling detail, but a public health imperative for reliable burden estimates and effective malaria control. Sub-optimum treatment masks the true burden of malaria, allowing hidden reservoirs to quietly fuel ongoing transmission—underscoring that only complete and effective treatment can break the cycle and achieve lasting control. Together, these findings underscore the need for integrated vector management strategies that target both adult and immature mosquito populations. Accordingly, public health policies should prioritize sustained ITN coverage, enhanced larval control, and immunity-preserving and enhancing interventions to reduce mortality and support sustained long-term malaria control.
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Taboe, Megan Sin, Afsana Yesmin, Eric Van Amber, Olivia Prosper Feldman, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6823359/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Malaria remains a significant global health challenge, with high morbidity and mortality. In endemic areas, repeated exposure improves partial immunity, leading to asymptomatic carriers with low parasitemia who act as hidden reservoirs, perpetuating transmission. This study develops a malaria transmission model with heterogeneous mosquito biting that integrates immunity dynamics to examine how repeated exposure influences immunity acquisition, transitions between symptomatic and asymptomatic states, and overall transmission patterns. Calibrated with annual confirmed case data from Kenya, the model is used to assess the effects of immunity dynamics, asymptomatic carriers, and insecticide-treated net (ITN) use or relaxation on malaria transmission, morbidity, mortality, and intervention efficacy across varying levels of immunity and exposure. Global sensitivity analysis and simulations of the model identify mosquito lifespan, recruitment rate, and infection probabilities as key transmission drivers, supporting integrated vector control and timely treatment to reduce cases and sustain population-level immunity. In particular, this study identifies adult mosquito mortality as the most influential factor in malaria transmission, highlighting the strong impact of interventions such as ITNs and indoor residual spraying (IRS). However, while these measures effectively reduce mosquito bites and transmission, they may inadvertently diminish clinical immunity, leaving individuals more vulnerable to severe disease upon future exposure. This concern is compounded by the presence of backward bifurcation, which indicates that reducing the basic reproduction number ($R_0$) below one may not be sufficient for elimination unless initial infection levels are also addressed. The study reveals that mosquito biting heterogeneity is a critical driver of immunity, disease dynamics, and altered intervention effectiveness--often misrepresented under uniform assumptions. Accurately capturing this variability is not just a modeling detail, but a public health imperative for reliable burden estimates and effective malaria control. Sub-optimum treatment masks the true burden of malaria, allowing hidden reservoirs to quietly fuel ongoing transmission—underscoring that only complete and effective treatment can break the cycle and achieve lasting control. Together, these findings underscore the need for integrated vector management strategies that target both adult and immature mosquito populations. Accordingly, public health policies should prioritize sustained ITN coverage, enhanced larval control, and immunity-preserving and enhancing interventions to reduce mortality and support sustained long-term malaria control. Applied Mathematics Mathematical and Theoretical Biology Asymptomatic malaria carriers Immunity boosted by repeated exposure Integrated malaria control Mosquito mortality Heterogeneous biting behavior Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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