The Second-Round Evaluation of Financial Incentives on Malaria Prevalence in the Lake Victoria Basin, Kenya: Updated Study Protocol for a Cluster-Randomized Controlled Trial

The Second-Round Evaluation of Financial Incentives on Malaria Prevalence in the Lake Victoria Basin, Kenya: Updated Study Protocol for a Cluster-Randomized Controlled Trial | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Second-Round Evaluation of Financial Incentives on Malaria Prevalence in the Lake Victoria Basin, Kenya: Updated Study Protocol for a Cluster-Randomized Controlled Trial Tomoya Matsumoto, Masaru Nagashima, Wataru Kagaya, Gordon Okomo, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4479731/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 Oct, 2025 Read the published version in Trials → Version 1 posted 5 You are reading this latest preprint version Abstract Background : Despite significant progress in global malaria reduction since 2000, driven primarily by supply-side interventions including improvements in bed nets and medication availability, recent years have seen a stagnation in this decline. In certain regions, cases have even increased (1). This trend is particularly concerning in high-burden areas such as Suba South Sub-county in Homa Bay County, Kenya, where malaria remains a persistent public health challenge. However, demand-side barriers—such as lack of knowledge of the disease and perceived costs of prevention and treatment among residents—have been relatively overlooked in control efforts. To address this gap, we conducted a cluster-randomized controlled trial (cRCT) to investigate the impact of an educational intervention and financial incentives on malaria-related behaviors (2). This second-round cRCT aims to build upon the first-round findings, with modifications to the experimental design and educational content to further explore the potential of demand-side interventions and inform future malaria control strategies. Methods : This second-round cRCT will re-randomize the original 92 clusters to either conditional cash transfer (CCT), lottery incentive scheme (LIS), or control arms. Each intervention arm will includeupdated malaria education and financial incentives linked to negative malaria test results, with reward amounts adjusted to reflect local inflation. We will re-assess malaria prevalence using RDT, microscopy, and PCR at three and six months post-intervention. The primary outcomes are changes in malaria prevalence, LLIN usage, and knowledge/perception of malaria. The analysis will combine data from both the first and second rounds to improve statistical power and provide a more comprehensive assessment of the intervention's impact. Discussion : This study addresses the limitations of the first-round trial by increasing statistical power and refining the educational component. By evaluating the effectiveness of demand-side interventions, we aim to inform policy and program design for malaria control in high-burden settings. The resulting evidence on the role of demand-side factors will complement traditional supply-side approaches, ultimately refining future malaria control policies and programs. This research, thereby, has the potential to contribute to the development of sustainable, community-based strategies for malaria elimination. Trial registration : UMIN000053284, registered on 6th January 2024. Malaria malaria education conditional cash transfer lottery incentive scheme Kenya cluster-randomized controlled trial Figures Figure 1 Figure 2 Administrative information Note: the numbers in curly brackets in this protocol refer to SPIRIT checklist item numbers. The order of the items has been modified to group similar items (see http://www.equator-network.org/reporting-guidelines/spirit-2013-statement-defining-standard-protocol-items-for-clinical-trials/). Title {1} The Second-Round Evaluation of Financial Incentives on Malaria Prevalence in the Lake Victoria Basin, Kenya: Updated Study Protocol for a Cluster-Randomized Controlled Trial Trial registration {2a and 2b}. University Hospital Medical Information Network (UMIN) Clinical Trials Registry, Japan, UMIN000053284, registered on 6th January 2024. Protocol version {3} Version 1.0 (26 May 2024) Funding {4} This work is supported by the Japan International Cooperation Agency (JICA), the Japan Agency for Medical Research and Development (AMED) under the Science and Technology Research Partnership for Sustainable Development Goals (SATREPS) program, JSPS KAKENHI (Grant Numbers JP21H051080 and 23KK0024), and KDDI Foundation (Grant Number unassigned). Author details {5a} Tomoya Matsumoto 1 , Masaru Nagashima 2 , Wataru Kagaya 3 , Gordon Okomo 4 , James Kongere 5 , Jared Oginga 5 , Victor Opiyo 5 , JesseGitaka 6 , Akira Kaneko 7 , 8,9 Department of Economics, Faculty of Commerce, Otaru University of Commerce, Hokkaido, Japan Institute of Developing Economies Japan External Trade Organization (IDE-JETRO), Chiba, Japan Department of Ecoepidemiology, Institute of Tropical Medicine (NEKKEN), Nagasaki University, Nagasaki, Japan Homa Bay County Government, Homa Bay, Kenya Centre for Research on Tropical Medicine and Community Development, Homa Bay, Kenya Directorate of Research and Innovation, Mount Kenya University, Thika, Kenya. Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden Department of Virology and Parasitology/Osaka International Research Center for Infectious Diseases, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan Department of Protozoology, Institute of Tropical Medicine (NEKKEN), Nagasaki University, Nagasaki, Japan # Joint senior authors Name and contact information for the trial sponsor {5b} Department of Economics, Otaru University of Commerce (OUC), Japan 3-5-21 Midori, Otaru, Hokkaido 047-8501, Japan TEL: +81-134-27-5210 Website: https://www.otaru-uc.ac.jp Directorate of Research and Innovation, Mount Kenya University (MKU), Kenya General Kago Road, Thika, Kiambu, Kenya Website: https://www.mku.ac.ke Institute of Developing Economies-Japan External Trade Organization (IDE-JETRO), Japan 3-2-2 Wakaba, Mihamaku, Chiba City, Chiba 2618545, Japan TEL: +81-43-299-9500 Website: https://www.ide.go.jp/ Role of sponsor {5c} OUC supports project management oversight, trial management, data management, statistical analysis, and research governance. MKU also holds overall authority together with project management and analysis. IDE-JETRO manages the KDDI Foundation’s research fund. Introduction Background and rationale {6a} Since around 2000, significant efforts have been made in combating malaria globally, particularly in Sub-Saharan Africa, where the disease burden is exceptionally high. Various programs have been put into practice to distribute long-lasting insecticide-treated bed nets (LLINs), implement indoor residuals spraying (IRS), promote the use of rapid diagnostic testing (RDT), and provide artemisinin-based combination therapy in the most endemic areas. Along with these efforts, global malaria control made substantial progress, reducing malaria deaths by one-third between 2000 and 2019, for example ( 1 ). However, recent years have seen this progress stall, with increased cases driven by complex factors, including disrupted service provision during the COVID-19 pandemic, insecticide and drug resistance, and funding shortfalls, among many others ( 1 ). Sustained and effective efforts are therefore considered crucial for continued progress in malaria elimination. Our study site is Homa Bay County in western Kenya, where malaria remains a critical public health challenge. Through our fieldwork, we have observed the roles played by the supply-side efforts such as those mentioned above. At the same time, we have identified potential socio-economic constraints that may pose significant barriers to effective malaria prevention and treatment by residents, who are the consumers of health care services. Such demand-side factors, including access to and knowledge of essential tools and services, can heavily influence health-seeking behavior and adherence to recommended strategies. For example, the economic literature has pointed out that people spend more for treatment than for prevention ( 3 ). Also, the prevention of infectious diseases such as malaria by one individual can reduce the risks of other individuals nearby, a property called a positive externality. In this case, people may be discouraged from taking preventive measures if they expect others to do so as well. This phenomenon, known as "free-riding," can undermine overall disease control efforts ( 4 – 6 ). Our team conducted an experimental intervention aimed at addressing these demand-side constraints ( 2 ). We targeted two crucial factors affecting the people’s demand: knowledge and cost of malaria prevention and early treatment. Employing a cluster randomized controlled trial (cRCT) design, we compared a conditional cash transfer (CCT) arm and a lottery incentive scheme (LIS) arm to a control group. The financial incentives were linked to malaria testing results and healthcare utilization (e.g., early treatment-seeking for suspected malaria cases). The intervention targeted households in 92 clusters in Suba South Sub-county, Homa Bay County. While the study indicated potential benefits, certain limitations necessitate a second-round intervention to refine our understanding of the intervention’s effectiveness. Our second-round intervention tackles a major challenge that hindered our first-round experiment. That is, the study's setting had a relatively low baseline malaria prevalence, limiting the minimum detectable effect size. Recognizing the significance of our research, we have secured additional funding to address these limitations. The second-round intervention will not only address prior limitations but also further explore crucial aspects of the demand-side approach to malaria control. Specifically, it will help identify the roles that knowledge and cost of malaria prevention play in household behaviors and practical challenges for effectively implementing and scaling the proposed program. In addition, preliminary analysis from the first-round intervention revealed that while the educational materials successfully increased bed net usage, this did not translate to a significant reduction in malaria prevalence. We hypothesize that this may be due to the already high baseline bed net usage rate in the region, suggesting that proper net usage and adherence to other preventive measures may require additional emphasis. These observations have motivated us to revise and update the educational materials for the second-round intervention to include not only messages promoting bed net use but also advice on their best practices and other supportive preventive measures. Furthermore, given the potential for substantial indirect effects of the intervention (i.e., spillover effects within households and clusters), we have increased the proportion of intervention households within each intervention cluster. This change aims to enhance our ability to gain a more comprehensive understanding of the intervention's overall impact. Objectives {7} The primary objective is to evaluate the causal impact of the financial incentive intervention on malaria prevalence in children aged zero to 15 and all age groups during 3- and 6-month follow-up periods. The secondary objectives during a 6-month follow-up period are To measure the impact of the financial incentive intervention on malaria preventive behaviors, especially bed net usage, To measure the impact on malaria knowledge, and To measure the spill-over effects from those exposed to the intervention to their geographic neighbors and those who are socially connected. Trial design {8} The study is the second round of a cRCT building upon a previous experiment ( 2 ). The first-round cRCT, conducted in Suba South Sub-county, Homa Bay, Kenya, employed a two-stage randomized design. In the first stage, clusters were randomly assigned to one of three arms: ( 1 ) CCT plus malaria education (EDU); ( 2 ) LIS plus EDU; or ( 3 ) a control group with no intervention. Each cluster consisted of 20 adjacent households based on household location information obtained from a census survey conducted prior to the first round of the experiment, from May to July 2021. The second stage of randomization occurred at the household level within intervention clusters to measure spillover effects. This second-round intervention will retain the same cRCT design and sample size, targeting the same clusters. However, treatment assignment will be re-randomized. For the second-round trial, we stratify clusters based on two factors: (a) baseline malaria prevalence among children under 15 years of age (as measured in the first-round baseline survey) and (b) their arm assignment in the first-round randomization. Clusters within each of these strata will then be randomly assigned to one of the three study arms (CCT, LIS, or control) using computer-generated random numbers. Figure 1 illustrates the locations and arm assignments of clusters for both the first and second rounds. Notably, the second-round stratification differs from the first round by including prior arm assignment and excluding the number of children under 15 as a stratification factor ( 2 ). Similar to the first round, the second-round intervention will employ a second stage of randomization at the household level within each intervention cluster (CCT or LIS). This will determine which households receive the treatment, allowing for the measurement of intra-cluster spillover effects. During a site visit, a household representative will draw a scratch card with a number from 1 to 10. Households drawing numbers 1–8 will receive the intervention, consisting of EDU and eligibility for either the CCT or LIS incentive, depending on their cluster's assigned arm. Households drawing 9 or 10 will not receive the intervention and will serve as intra-cluster controls. The power analysis of this experiment combines the effect estimates from the first- and second-round experiments, each of which is closely related but conceptually independent. That is, each experiment provides a treatment effect estimate given the size of the expected intervention effect and the two-step randomization design, following the newly developed regression models employing a random saturation experiment ( 7 ). The two intervention arms, CCT and LIS, are randomly assigned to 32 clusters, respectively, while the control arm is assigned to 28 clusters. This overall structure of the experiment forms a two-stage randomized control trial. The two estimates from two randomization samples drawn from the same population are then synthesized to one parameter estimate using a meta-analysis approach. Methods: Participants, interventions, and outcomes Study setting {9} The study will be conducted in Suba South Sub-County, Homa Bay County, Kenya. As of the 2019 national census, the sub-county had a population of 122,383 in 27,635 households, primarily composed of the Luo and Suba ethnic groups ( 8 ). The primary occupations are fishing and farming. Housing typically consists of multiple structures, with mud walls and metal sheet roofs being the most common, although iron sheets, concrete, or stone construction can also be found ( 8 ). The Lake Victoria region generally experiences two rainy seasons annually: a long rainy season from March to June and a shorter one from August to October, although recent years have seen irregular patterns. Malaria incidence peaks one to two months after these rainy periods, with Anopheles (An.) gambiae s.s., An. arabiensis , and An. funestus being the primary vectors ( 9 ). Suba South Sub-County is served by 30 public health facilities, including two Sub-county hospitals, eight health centers, and 20 dispensaries. The sub-county is divided into community health units, each monitored by a community health promoter (CHP) responsible for malaria case detection and treatment using RDTs and ACTs, respectively. The government periodically distributes LLINs free of charge, with the most recent distribution completed in 2023/2024. Eligibility criteria {10} Eligibility for the second-round intervention will be based on participation in the first-round experiment ( 2 ). All households that participated in the first-round baseline survey and provided consent for the follow-up surveys will be eligible for inclusion in the second round, regardless of their experimental arms in the original study. For detailed inclusion and exclusion criteria, please refer to our previous protocol ( 2 ) and Table 1 below. Table 1 Inclusion and exclusion criteria for the intervention and prospective cohort survey Inclusion criteria Exclusion criteria First-round Baseline (survey) At least one permanent resident aged 18 years or older in the household Informed consent provided by at least one adult in the household Baseline (blood sampling) Members residing in the households participated in the baseline survey Severe chronic illnesses Informed consent provided by the parent or guardian before each survey Second-round financial incentive intervention Household members residing in the households participated in the baseline survey Informed consent provided by at least one adult in the household Second-round follow-up 1 (survey) Households participated in the baseline survey Informed consent provided by at least one adult in the household Second-round follow-up 1 (blood sampling) Household members residing in the households participated in the baseline survey Severe chronic illnesses Informed consent provided by the parent or guardian before each survey Second-round follow-up 2 (survey) Households participated in the baseline survey Informed consent provided by at least one adult in the household Second-round follow-up 2 (blood sampling) Household members residing in the households participated in the baseline survey Severe chronic illnesses Informed consent provided by the parent or guardian before each survey Who will take informed consent? {26a} Written informed consent will be obtained by trained study team members who are fluent in Luo (a local language), Swahili, and English, and have a thorough understanding of the study protocol. After confirming eligibility, these team members will present potential participants with a comprehensive information sheet detailing the study’s purpose and contents as well as their right to withdraw at any time. The information sheet will be available in both Luo and English. For participants who are unable to read, the information will be conveyed verbally by a study team member. Participants will be given ample opportunity to ask questions and discuss any concerns before being asked to provide their consent. Written consent will be obtained only after the participant demonstrates a clear understanding of the study and voluntarily agrees to participate. Additional consent provisions for collection and use of participant data and biological specimens {26b} In addition to the study overview, the study information sheet will provide detailed information regarding the collection, storage, and use of personal data and biological specimens obtained during baseline and follow-up surveys, as well as blood sampling procedures. Interventions Explanation for the choice of comparators {6b} LLINs are the most widely used malaria preventive measure in Kenya. The Kenya National Malaria Control Programme coordinates free LLIN distribution every three years, and county governments are responsible for delivery to residents in endemic areas. As all target households in this trial will have unrestricted access to LLINs through this program, the control group will reflect the current standard of prevention and care in the region. The primary purpose of this trial is to evaluate the incremental effect of financial incentives combined with malaria education on top of existing LLIN coverage and usual care practices. Therefore, the control group households are expected to engage in standard malaria prevention and treatment-seeking behaviors, including LLIN use, as dictated by the national program and individual choices. Intervention description {11a} Our survey teams will visit households in all target clusters. For households in the control clusters, the teams will explain the upcoming follow-up survey at three and six months, confirm continued study participation, and conduct a short interview. In the intervention clusters, the team will also explain the follow-up surveys and confirm participation, but additionally inform households that they are part of a pilot intervention. They will then explain that eligibility for the intervention will be determined by a scratch card draw, with numbers 1–8 qualifying for the intervention (malaria education and a financial incentive) and numbers 9–10 not. The survey team will ensure the household representative understands the incentive scheme before the draw and will re-explain if necessary. For households selected for the intervention through the scratch card draw, the survey team will explain the specific reward scheme and the timing of the follow-up surveys at three and six months, and their members are invited to watch the malaria education material on a tablet device and then proceed to a short interview. Households unselected for the intervention will be informed that they will not receive the intervention and proceed to a short interview only. The detailed instruction script for enumerators throughout this intervention process is provided in Appendices 1 and 2. Criteria for discontinuing or modifying allocated interventions {11b} Given the low-risk nature of the financial incentive intervention and the absence of anticipated direct health risks, discontinuation of the intervention for individual participants will primarily occur under two circumstances. They include participant request (when a participant explicitly requests to withdraw from the study) and loss to follow-up (when a participant is lost to follow-up, including migration). Crossover from the control arm to the intervention arm will not be permitted during the follow-up period. Participants who migrate between study arms or emigrate from the study areas will be dropped from the study follow-up. Strategies to improve adherence to interventions {11c} In this study, adherence refers to the continued participation of individuals from both intervention-eligible and intervention-ineligible households throughout the follow-up period. Adherence will be monitored during the follow-up surveys by confirming the presence of participants and collecting the required blood samples. Relevant concomitant care permitted or prohibited during the trial {11d} There are no restrictions on concomitant care during the trial. All study participants, regardless of their assigned arm, are permitted to continue their usual healthcare practices, including the use of freely distributed LLINs and access to standard malaria testing and care through both public and private healthcare providers. Provisions for post-trial care {30} All study participants will remain under the standard care of the existing health system in Homa Bay County throughout and after the trial. Given the low-risk nature of the intervention, no specific post-trial care is anticipated to be necessary beyond the usual medical services available in the community. Outcomes {12} The primary outcomes of the study are (i) malaria prevalence by PCR in children and adults at three and six months post-intervention, (ii) change in the use of LLIN at three and six months post-intervention, and ( 3 ) change in malaria knowledge and perception among community residents at three and six months post-intervention. The secondary outcome is malaria prevalence by RDT in children and adults at three and six months post-intervention. Participant timeline {13} This study is the second round of a cRCT evaluating the impact of educational and financial incentives on malaria prevention and treatment behaviors ( 2 ). The first round of the study included the recruitment of participants and the collection of baseline data. As such, no additional recruitment is planned for this second round. Instead, the existing cohort of participants will be re-randomized into intervention and control arms to assess the effectiveness of a refined intervention. This sequential approach allows us to build upon the existing data and infrastructure, maximizing efficiency and minimizing disruption to the community. Table 2 Study timeline STUDY PERIOD Enrolment Allocation Post-allocation Close-out TIMEPOINT (month) -19 0 3 6 18 ENROLMENT : Eligibility screen X Informed consent X Allocation X INTERVENTIONS : Education + Incentivization (CCT) X Education + Incentivization (LIS) X ASSESSMENTS : Questionnaire survey X X X X X Capillary blood sampling by lab tech X X X Sample size {14} Based on an independent survey conducted concurrently in our study area, the estimated malaria RDT positivity rate is approximately 30%. With an average household size of 5 (as per our census data), we aim to detect a combined direct and spillover effect of our intervention, resulting in a 19.6% (or 5.89 percentage-point, ppt) reduction in RDT positivity for directly treated individuals and a 21.0% (or 6.30 ppt) reduction for untreated individuals within intervention clusters. We retain the same cluster definitions and sample size as the first-round intervention ( 2 ), totalling 9,200 individuals from 1,840 households grouped into 92 clusters. With no results from the previous study yet available, the sample size and treatment assignment probabilities are calculated ex-ante. To achieve sufficient statistical power to detect the aimed effect sizes, we require a 27.32% RDT positivity reduction (or 8.20 ppt) for directly treated individuals and a 31.49% reduction (or 9.45 ppt) for untreated individuals within intervention clusters. Our calculation based on the optimal saturation design ( 7 ) assumes a power of 0.8, a two-sided type-I error of 5%, a cluster size of 20 households, and an intra-cluster correlation coefficient of 0.05. This calculation results in 28 clusters randomly assigned to the control condition and 32 clusters to each intervention condition (CCT and LIS). Within each intervention cluster,16 households are expected to receive the treatment, while the remaining four will serve as untreated controls. The two intervention arms will be compared to the control arm to assess their relative effectiveness. Recruitment {15} No new participants will be recruited for this second-round intervention. All households participating in the first-round study will be included in the second round, provided that they meet the continued eligibility criteria. For details on the initial recruitment, community sensitization, and census procedures, please refer to our previous protocol ( 2 ). Assignment of interventions: allocation Sequence generation {16a} A new set of random numbers, independent of those generated in the first round, will be generated in the for each cluster using the statistical software R. These numbers will follow a uniform distribution between 0 and 1 with the seed set to the date of randomization in ‘ yyyymmdd ’ format (e.g., 20240321 for March 21st, 2024). R’s built-in functions set.seed() and runif() will be used for this procedure. Concealment mechanism {16b} Following stratification based on the malaria prevalence among children under 15 and the first-round intervention arm, a random number will be assigned to each cluster. The stratification creates six strata (2 x 3). Within each stratum, clusters will be sorted in ascending order based on their assigned random numbers. The clusters with the lowest random numbers (four to five per stratum) will be assigned to the control arm, followed by the CCT arm (five to six per stratum), and finally the LIS arm (five to six per stratum). This will result in a total of 28 control clusters, 32 CCT clusters, and 32 LIS clusters. Implementation {16c} A designated team member will generate the cluster-level allocation sequence on the day the intervention begins. Local study assistants will enroll participants and implement the assigned interventions in the respective clusters. Assignment of interventions: Blinding Who will be blinded {17a} Cluster-level arm assignment will not be disclosed to trial participants. However, due to social interactions, participants may become aware of different arm assignments across clusters. We will assess the extent of this information flow through surveys. Within intervention arms (CCT and LIS), household representatives will be aware of their household’s treatment status due to the lottery scratch card randomization. Study team members participating in field activities cannot be blinded due to their involvement in cluster and household randomization. However, laboratory- and office-based personnel (e.g., microscopists and laboratory technicians) will remain blinded to participant identity and intervention status, as biological specimens will be identified by unique numeric study identifiers, and personal information will be removed before analyses. Procedure for unblinding if needed {17b} As this is a low-risk socio-economic intervention with no anticipated physical risks to participants, the need for unblinding procedures is currently not foreseen. Data collection and management Plans for assessment and collection of outcomes {18a} Malaria prevalence will be estimated using cross-sectional malariometric surveys. The baseline survey was conducted at the beginning of the first-round study, and two follow-up surveys for the second-round experiment will be conducted approximately three and six months post-intervention. Malaria status will be determined using RDT, microscopy, and PCR, following the same procedures as described in the first-round protocol ( 2 ). Malaria incidence will be assessed at both three- and six-month follow-up surveys, using the same procedure as described in the first-round protocol ( 2 ). During household visits, enumerators will administer a structured questionnaire to each participating household, collecting data on any history of fever, malaria episodes, or visits to local health facilities within the previous three months ( 10 ). Enumerators and certified medical laboratory staff will be trained on the questionnaire's content and the use of the CSPro application data collection, adhering to the same procedures outlined in our first protocol ( 2 ). This includes built-in validation and completion checks to ensure data quality and completeness. To avoid duplication, all sample collection materials, such as microscope slides, filter papers, and sample tubes, will be pre-labeled with auto-generated serial numbers. The CSPro application will prompt staff to confirm participant identity and serial number before blood sampling, and the completeness of sampling will be verified twice: in the field and at the laboratory. Plans to promote participant retention and complete follow-up {18b} We will employ the same participant retention and follow-up strategies that proved successful in our first-round intervention ( 2 ). Specifically, our survey team will schedule household visits in advance, confirming the date and time with participants at least one week prior. CHPs will report any participant concerns or issues to the research team, and collaborative discussions will be held to address these issues promptly. Additionally, the research team will periodically accompany enumerators during household visits to reinforce the importance of the study and maintain participant engagement. To enhance participant retention, we will implement a multi-faceted approach incorporating culturally tailored strategies, reflecting our established relationship with the community. This will include regular SMS and phone call reminders to participants, as well as personalized home visits by CHPs. These CHPs will serve as a trusted point of contact, addressing any questions or concerns participants may have and reinforcing the importance of their continued participation. Data management {19} Data management for this second-round intervention will largely follow the established procedures from the first round, as detailed in our previous protocol ( 2 ). Data will be collected on Android-based tablets using the CSPro application, incorporating built-in data validation checks. Follow-up survey data will be uploaded to the CSPro server, and after quality verification by data managers, local data will be deleted from the tablets to prevent overwriting. Each visit will be pre-programmed within CSpro for streamlined data entry. Specially trained enumerators who are locally hired and familiar with the participants will conduct the interviews, verifying participant identity before data entry. Data managers will perform periodic data quality checks on the server. Access to the survey data will be restricted to the study’s data analysts and managers. Confidentiality {27} To maintain confidentiality, each study participant is assigned a unique identifier. Personally identifiable information unnecessary for data analysis will be removed. The anonymized data will be stored separately from the key linking personal information on a secure server accessible only to authorized research staff. While publications will primarily contain aggregated data, anonymized individual-level data may also be included to enhance transparency and reproducibility, ensuring that no personally identifiable information can be derived from the published information. Plans for collection, laboratory evaluation and storage of biological specimens for genetic or molecular analysis in this trial/future use {33} Blood samples will be collected to examine malaria infection status using multiple methods, characterize immune responses to malaria parasites and mosquito saliva, and conduct malaria parasite genomic analyses. No human genetic studies are planned for this study. However, any remaining biological specimens after these analyses will be stored indefinitely for future research purposes unless the participants explicitly opt out during the informed consent process. Participants are provided with the study team’s contact information in the consent form and may withdraw from this study or any future research using their samples at any time without penalty or loss of benefits. Statistical methods Statistical methods for primary and secondary outcomes {20a} The intention-to-treat (ITT) analysis will be the primary approach for both the primary and secondary outcomes. The impact of the intervention on these outcomes will be assessed using the regression framework as proposed by the prior study for a two-stage cRCT ( 7 ). This analysis will allow us to estimate the ITT effects, both direct and spillover, on treated and untreated households within a cluster while controlling for potential confounders such as age, gender, house structure, and socioeconomic indicators. A similar regression approach will be employed for the analysis of secondary outcomes. As a supplementary analysis, we plan to conduct and a per-protocol analysis, which will include only those participants who adhere to the study protocol and complete all required follow-up assessments. This analysis will provide additional insights into the intervention’s effect under ideal conditions of full compliance. In addition to the primary and secondary analyses for the second-round intervention, we plan to conduct a combined analysis of the data from both the first and second rounds. This analysis will leverage Bayesian updating techniques to integrate the findings from both studies and obtain a more precise and comprehensive estimate of the intervention. Interim analyses {21b} We do not plan an interim analysis. Methods for additional analyses (e.g., subgroup analyses) {20b} Given the known association between malaria risk and socioeconomic factors ( 11 ), we plan to conduct subgroup analyses to explore potential heterogeneity in the intervention’s effects across different socioeconomic backgrounds. These analyses will utilize relevant socioeconomic indicators collected during the baseline survey. The same regression model employed for the primary analysis ( 7 ) will be used to estimate treatment effects within each subgroup. If feasible, we intend to assess the interaction between the intervention and socioeconomic variables to formally test whether the intervention’s effect differs across subgroups defined by socioeconomic variables. Methods in analysis to handle protocol non-adherence and any statistical methods to handle missing data {20c} Once all data collection is completed, the extent and patterns of missing data will be assessed. If necessary, multiple imputation methods may be used to handle missing data. Plans to give access to the full protocol, participant-level data and statistical code {31c} This manuscript is the full protocol. The authors will create anonymized datasets. Future statistical codes will be made available upon reasonable request. Oversight and monitoring Composition of the coordinating centre and trial steering committee {5d} A coordinating centre has been established to oversee the trial's day-to-day operations. This centre includes a communication group comprising enumerators and laboratory technicians, who exchange experiences and address operational challenges. A local management team, consisting of study investigators from Kenya and Japan, provides guidance and ensures sample and data integrity. A steering committee, composed of key researchers from Kenya and Japan, including the principal investigator (PI) and co-PI, will convene monthly meetings to monitor overall trial progress and make strategic decisions. Composition of the data monitoring committee, its role and reporting structure {21a} Given the low-risk nature of the intervention, a formal data monitoring committee has not been established for this study. However, to ensure data quality and methodological rigor, the research team will consult with an independent statistician as needed for additional review and validation of statistical analyses. Adverse event reporting and harms {22} The financial incentives and malaria education are not expected to pose significant risks. However, should any adverse events occur during the study period, participants will be instructed to report to their designated CHP, who will then promptly inform the research team and Homa Bay County Ministry of Health (MOH). MOH’s medical officers will assess the relatedness of each reported event. In the event of a serious adverse event suspected to be study-related, the PI will be immediately notified, and the study team, in consultation with the MOH and Homa Bay County Teaching and Referral Hospital representatives, will convene an urgent meeting to review the case and determine its relatedness to the study. Appropriate action, such as protocol modifications, additional medical care, or study termination, will be taken if the case is deemed related to the study and considered to do excessively more harm than good to participants and communities. Frequency and plans for auditing trial conduct {23} Regular monitoring will occur throughout the study to ensure adherence to the protocol and data quality. This can include a pre-implementation review of all study procedures, monthly progress meetings during follow-up, annual reports and renewal applications to the relevant IRBs (Otaru University of Commerce, Japan, and Mount Kenya University, Kenya), and regular data quality checks. Plans for communicating important protocol amendments to relevant parties (e.g., trial participants, ethical committees) {25} Any substantial protocol modifications that may impact the study’s conduct, potential benefits or harm to participants, or participant safety will be submitted to the relevant institutional review boards (IRBs) at Mount Kenya University and Otaru University of Commerce for approval prior to implementation. Upon approval, such amendments will be communicated to study participants and updated in the trial registry. Minor amendments not impacting participant safety or study validity will be documented and reported to the IRBs. Dissemination plans {31a} The results of this study will be shared with relevant stakeholders, including the Homa Bay County Government and Kenya National Malaria Control Program, to discuss the potential for scaling up the intervention. Findings will also be disseminated through peer-reviewed publications and presentations at scientific conferences, with the aim of informing the development of novel malaria control strategies in other malaria-endemic regions. Furthermore, feedback from research participants will be actively sought and incorporated into future refinements of the intervention, ensuring its continued relevance and acceptability within the community. Discussion Despite significant progress in global malaria reduction since 2000, recent years have witnessed a stagnation in this decline, with cases even increasing in certain regions ( 1 ). This trend is particularly concerning in high-burden areas such as Suba South Sub-county in Homa Bay County, Kenya, where malaria remains a persistent public health challenge. While past efforts have focused largely on increasing the availability of malaria prevention and treatment tools, our research seeks to investigate the impact of addressing demand-side barriers to their uptake and utilization. Although our previous experimental study provided a promising framework for an educative and incentivized intervention to improve malaria prevention and treatment behaviors, limitations in sample size and baseline malaria prevalence hindered our ability to draw definitive conclusions. Therefore, this second-round intervention thus seeks to address these shortcomings, aiming to provide a more robust assessment of the impact of parental education and financial incentives on children's malaria control within this specific context. We propose a second-round cRCT experiment to investigate the impact of demand-side interventions on malaria control. We aim to expand upon our prior research, which examined the effectiveness of combined educational and incentive-based interventions in promoting malaria prevention among young children. Mirroring the initial study, the second-round intervention will retain the cluster-randomized design and sample size, targeting the same 92 clusters within Suba South Sub-county. The educational materials will be enhanced by incorporating practical guidance on malaria prevention, such as bed net maintenance, addressing a gap identified in our previous work. We will also continue to investigate the effectiveness of the financial incentive schemes (CCTs and LIS), adjusting reward amounts to 300 KSh (CCT) and 3,000 KSh (10% chance of winning for LIS) to align with current treatment costs and local inflation rates. The program's effect will be assessed not only within this second-round cRCT but also through a combined analysis with the first-round intervention, yielding a more comprehensive understanding of the overall experimental impact, which will in part address one of the limitations of the first-round intervention that a tight sample size and the low baseline prevalence lowered our statistical power to detect the true program effect. The goal of this approach is to increase uptake of preventive measures and early treatment through optimized incentives, thereby reducing the overall burden of malaria. This second-round intervention has the potential to significantly inform malaria control policies and programs. By generating robust evidence on the effectiveness of demand-side interventions, particularly educational and incentive-based strategies, our research can guide the development of scalable, practical solutions for malaria elimination. The insights gained will contribute to a growing body of evidence-based approaches, ultimately impacting the lives of countless individuals at risk of this devastating disease. Trial status Recruitment of the current second-round intervention is based on the first-round trial which started on January 7, 2022, and the final subject enrolment was completed on March 8, 2022 (see also Table 3). The second-round intervention plans two follow-up surveys. The first is planned to take place through May and July 2024, and the second through August and October 2024. The progress of the first-round intervention is also listed for transparency purposes. The first-round intervention started on June 18, 2022, and ended on July 29, 2022. The first-round follow-up survey started on December 19, 2022, and ended on February 10, 2023. The current protocol is version 1.0 of May 26, 2024. This study represents the second round of a cRCT building upon the previous experiment ( 2 ). Since participant recruitment was completed during the first round, it was not possible to submit this protocol manuscript before recruitment completion. However, this submission occurs before the post-allocation follow-up surveys, aligning with the journal's criteria of submission before the last patient/last visit. Importantly, this second round trial aims to address a limitation of the first round, namely the unexpectedly low statistical power due to the lower-than-anticipated baseline malaria prevalence, by re-randomization and collection of additional data to provide a more robust assessment of the intervention’s effectiveness. By addressing the limitations of the first round and strengthening the evidence base for demand-side interventions, this study will inform the development of more effective malaria control policies and programs, ultimately benefiting both the scientific community and the populations most affected by this disease. For details on the study timeline, please refer to Fig. 2 (Study flowchart and sampling timeline) and Tables 2 (Study timeline) and 3 (Trial status and plan). Table 3 Trial status and plan Action Date The date of the first enrolment (baseline) January 7, 2022 Finalize the enrolment (baseline) March 8, 2022 Start the first-round intervention June 18, 2022 Complete the first-round intervention July 29, 2022 Start the first-round follow-up survey December 19, 2022 Complete the first-round follow-up survey February 10, 2023 Start the second-round intervention January 14, 2024 Complete the second-round intervention February 23, 2024 Start the second-round follow-up survey 1 May 27, 2024 Complete the second-round follow-up survey 2 July 2024 Start the second-round follow-up survey 2 August 2024 Complete the second-round follow-up survey 2 October 2024 Abbreviations LLIN long-lasting insecticide-treated net PBO piperonyl butoxide ITN Insecticide-treated net RDT rapid diagnostic test ACT artemisinin combination therapy CHP community health promoter CCT conditional cash transfer LIS lottery incentive scheme EDU malaria education using the original animated tablet-based material (12) Declarations Acknowledgements We would like to express our sincere gratitude to this study's participants, field, and laboratory staff. We also acknowledge the collaboration and support of health offices in Homa Bay County, Kenya. Authors’ contributions {31b} AK is the principal investigator, and JG is the co-principal investigator. TM, MN, and AK developed the original study concept. TM, MN, WK, JK, JO, VO, JG, and AK participated in discussions and contributed to the study protocol. TM, MN, JO, and VO drafted the manuscript. WK, GO, JK, JG, and AK provided critical revisions of the manuscript. All authors read and approved the final manuscript. Funding {4} This study received support from the JICA/AMED joint research project (SATREPS, Grant No. 20JM0110020H0002) [to AK and JG], JSPS KAKENHI (Grant No. JP21H051080 and 23KK0024) [to TM]. the KDDI Foundation (project title ‘E-Learning, Mobile Transfer, and Malaria Elimination’) [to MN]. The funders had no role in the study design, data collection and analysis, interpretation, the decision to publish, or the preparation of the manuscript. Availability of data and materials {29} The study regimen, consent forms, assent forms, and study-related materials will be accessible from the corresponding author upon reasonable request. The final trial dataset will be made available to all investigators involved in the study. Anonymized datasets and relevant analysis scripts will be published in a data repository and made available upon completion of the data analysis and manuscript preparation. Ethics approval and consent to participate {24} This study is approved by the Mount Kenya University Independent Ethics and Research Committee (MKU-IERC) (approval number: MKU/ERC/2165) and the Ethics Committee at Otaru University of Commerce (approval number: OUC-2020-07-01). Consent will be sought from study participants before the experimental intervention is implemented. Participants have the right to withdraw from the study at any time and the option to withhold previously collected samples from any future analyses and studies. The consent form clearly states that the samples collected in this study may potentially be used for other research purposes. In such cases, we will obtain the necessary ethical approval and allow participants to opt out. All experiments will be carried out in adherence to WHO requirements and the Declaration of Helsinki. Consent for publication {32} Not applicable - no identifying images or other personal or clinical details of participants are presented here or will be presented in reports of the trial results. The participant information materials and informed consent forms are available from the corresponding author on request. Competing interests {28} The authors have no competing interests to disclose. References World Health Organization. World Malaria Report 2023. Geneva: World Health Organization; 2023. Matsumoto T, Nagashima M, Kagaya W, Kongere J, Gitaka J, Kaneko A. Evaluation of a financial incentive intervention on malaria prevalence among the residents in Lake Victoria basin, Kenya: study protocol for a cluster-randomized controlled trial. Trials. 2024;25(1):165. Dupas P, Miguel E. Chapter 1 - Impacts and Determinants of Health Levels in Low-Income Countries. In: Banerjee AV, Duflo E, editors. Handbook of Economic Field Experiments [Internet]. North-Holland; 2017. pp. 3–93. https://www.sciencedirect.com/science/article/pii/S2214658X16300113 . Cohen J, Dupas P. Free Distribution or Cost-Sharing? Evidence from a Randomized Malaria Prevention Experiment*. Q J Econ. 2010;125(1):1–45. Ibuka Y, Li M, Vietri J, Chapman GB, Galvani AP. Free-Riding Behavior in Vaccination Decisions: An Experimental Study. Boni MF, editor. PLoS ONE. 2014;9(1):e87164. Corey White. Measuring Social and Externality Benefits of Influenza Vaccination. J Hum Resour. 2021;56(3):749. Baird S, Bohren JA, McIntosh C, Özler B. Optimal Design of Experiments in the Presence of Interference. Rev Econ Stat. 2018;100(5):844–60. Kenya National Bureau of Statistics, editor. 2019 Kenya Population and Housing Census Volume II: Distribution of Population by Administrative Units. Nairobi: Kenya National Bureau of Statistics; 2019. Futami K, Dida GO, Sonye GO, Lutiali PA, Mwania MS, Wagalla S, et al. Impacts of insecticide treated bed nets on Anopheles gambiae s.l. populations in Mbita district and Suba district, Western Kenya. Parasites Vectors. 2014;7(1):63. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–81. Degarege A, Fennie K, Degarege D, Chennupati S, Madhivanan P. Improving socioeconomic status may reduce the burden of malaria in sub Saharan Africa: A systematic review and meta-analysis. Carvalho LH, editor. PLoS ONE. 2019;14(1):e0211205. Nyqvist MB, Corno L, de Walque D, Svensson J. Incentivizing Safer Sexual Behavior. Am Economic Journal: Appl Econ. 2018;10(3):287–314. Supplementary Files Appendix1.docx Cite Share Download PDF Status: Published Journal Publication published 21 Oct, 2025 Read the published version in Trials → Version 1 posted Editorial decision: Minor revision 18 Oct, 2024 Reviewers agreed at journal 20 Jul, 2024 Reviewers invited by journal 18 Jul, 2024 Editor assigned by journal 09 Jul, 2024 First submitted to journal 17 Jun, 2024 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4479731","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":328679677,"identity":"21c44d76-d224-4f95-83b6-a5fdbf61569e","order_by":0,"name":"Tomoya Matsumoto","email":"","orcid":"","institution":"Otaru University of Commerce: Otaru Shoka Daigaku","correspondingAuthor":false,"prefix":"","firstName":"Tomoya","middleName":"","lastName":"Matsumoto","suffix":""},{"id":328679678,"identity":"f62a62c7-e6d3-447c-8675-3e2e438dbd63","order_by":1,"name":"Masaru 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Daigaku","correspondingAuthor":false,"prefix":"","firstName":"Akira","middleName":"","lastName":"Kaneko","suffix":""}],"badges":[],"createdAt":"2024-05-26 10:53:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4479731/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4479731/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13063-025-09146-5","type":"published","date":"2025-10-21T16:16:59+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62660159,"identity":"25cc0c17-e2b2-42b6-8d13-e7b9234e747c","added_by":"auto","created_at":"2024-08-17 02:31:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":108619,"visible":true,"origin":"","legend":"\u003cp\u003eMap of Suba South showing the locations and the types of arms of the 92 trial clusters in the first-round (left) and second-round (right) experimental interventions.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4479731/v1/7998f81b8aab9db4ebee3562.png"},{"id":62660158,"identity":"d02fe706-5408-4641-8dd7-a36d4b215262","added_by":"auto","created_at":"2024-08-17 02:31:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":52067,"visible":true,"origin":"","legend":"\u003cp\u003eThe study flowchart and sampling timeline.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4479731/v1/77cdb0ab8b140c6c0abda51a.png"},{"id":94490239,"identity":"b54b1945-dc3b-45de-8522-bee94243f649","added_by":"auto","created_at":"2025-10-27 17:08:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1852531,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4479731/v1/b967c8f7-850d-47a1-8022-e4f3f9a0d66f.pdf"},{"id":62660161,"identity":"383fa9e1-4694-4e0b-9ca4-8ab74026767b","added_by":"auto","created_at":"2024-08-17 02:31:38","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":18265,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4479731/v1/b1ca9bfe364f36b64a6006b1.docx"}],"financialInterests":"","formattedTitle":"The Second-Round Evaluation of Financial Incentives on Malaria Prevalence in the Lake Victoria Basin, Kenya: Updated Study Protocol for a Cluster-Randomized Controlled Trial","fulltext":[{"header":"Administrative information","content":"\u003cp\u003eNote: the numbers in curly brackets in this protocol refer to SPIRIT checklist item numbers. The order of the items has been modified to group similar items (see http://www.equator-network.org/reporting-guidelines/spirit-2013-statement-defining-standard-protocol-items-for-clinical-trials/).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"639\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.11580594679186%\" valign=\"top\"\u003e\n \u003cp\u003eTitle {1}\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"65.88419405320813%\" valign=\"top\"\u003e\n \u003cp\u003eThe Second-Round\u0026nbsp;Evaluation of\u0026nbsp;Financial\u0026nbsp;Incentives\u0026nbsp;on\u0026nbsp;Malaria\u0026nbsp;Prevalence in\u0026nbsp;the\u0026nbsp;Lake Victoria\u0026nbsp;Basin, Kenya:\u0026nbsp;Updated Study\u0026nbsp;Protocol for a\u0026nbsp;Cluster-Randomized\u0026nbsp;Controlled\u0026nbsp;Trial\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.11580594679186%\" valign=\"top\"\u003e\n \u003cp\u003eTrial registration {2a and 2b}.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"65.88419405320813%\" valign=\"top\"\u003e\n \u003cp\u003eUniversity Hospital Medical Information Network (UMIN) Clinical Trials Registry, Japan, UMIN000053284, registered on\u0026nbsp;6th\u0026nbsp;January\u0026nbsp;2024.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.11580594679186%\" valign=\"top\"\u003e\n \u003cp\u003eProtocol version {3}\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"65.88419405320813%\" valign=\"top\"\u003e\n \u003cp\u003eVersion 1.0 (26 May 2024)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.11580594679186%\" valign=\"top\"\u003e\n \u003cp\u003eFunding {4}\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"65.88419405320813%\" valign=\"top\"\u003e\n \u003cp\u003eThis work is supported by the Japan International Cooperation Agency (JICA), the Japan Agency for Medical Research and Development (AMED) under the Science and Technology Research Partnership for Sustainable Development Goals (SATREPS) program,\u0026nbsp;JSPS KAKENHI (Grant Numbers\u0026nbsp;JP21H051080\u0026nbsp;and 23KK0024), and KDDI Foundation (Grant Number unassigned).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.11580594679186%\" valign=\"top\"\u003e\n \u003cp\u003eAuthor details {5a}\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"65.88419405320813%\" valign=\"top\"\u003e\n \u003cp\u003eTomoya Matsumoto\u003csup\u003e1\u003c/sup\u003e, Masaru Nagashima\u003csup\u003e2\u003c/sup\u003e, Wataru Kagaya\u003csup\u003e3\u003c/sup\u003e, Gordon Okomo\u003csup\u003e4\u003c/sup\u003e, James Kongere\u003csup\u003e5\u003c/sup\u003e,\u0026nbsp;Jared Oginga\u003csup\u003e5\u003c/sup\u003e, Victor Opiyo\u003csup\u003e5\u003c/sup\u003e,\u0026nbsp;JesseGitaka\u003csup\u003e6\u003c/sup\u003e, Akira Kaneko\u003csup\u003e7\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e8,9\u003c/sup\u003e\u003c/p\u003e\n \u003col\u003e\n \u003cli\u003eDepartment of Economics, Faculty of Commerce, Otaru University of Commerce, Hokkaido, Japan\u003c/li\u003e\n \u003cli\u003eInstitute of Developing Economies Japan External Trade Organization (IDE-JETRO), Chiba, Japan\u003c/li\u003e\n \u003cli\u003eDepartment of Ecoepidemiology, Institute of Tropical Medicine (NEKKEN), Nagasaki University, Nagasaki, Japan\u003c/li\u003e\n \u003cli\u003eHoma Bay County Government, Homa Bay, Kenya\u003c/li\u003e\n \u003cli\u003eCentre for Research on Tropical Medicine and Community Development, Homa Bay, Kenya\u003c/li\u003e\n \u003cli\u003eDirectorate of Research and Innovation, Mount Kenya University, Thika, Kenya.\u003c/li\u003e\n \u003cli\u003eDepartment of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden\u003c/li\u003e\n \u003cli\u003eDepartment of Virology and Parasitology/Osaka International Research Center for Infectious Diseases, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan\u003c/li\u003e\n \u003cli\u003eDepartment of Protozoology, Institute of Tropical Medicine (NEKKEN), Nagasaki University, Nagasaki, Japan\u003c/li\u003e\n \u003c/ol\u003e\n \u003cp\u003e# Joint senior authors\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.11580594679186%\" valign=\"top\"\u003e\n \u003cp\u003eName and contact information for the trial sponsor {5b}\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"65.88419405320813%\" valign=\"top\"\u003e\n \u003cp\u003eDepartment of Economics, Otaru University of Commerce (OUC), Japan\u003c/p\u003e\n \u003cp\u003e3-5-21 Midori, Otaru, Hokkaido 047-8501, Japan\u003c/p\u003e\n \u003cp\u003eTEL: +81-134-27-5210\u003c/p\u003e\n \u003cp\u003eWebsite: https://www.otaru-uc.ac.jp\u003c/p\u003e\n \u003cp\u003eDirectorate of Research and Innovation, Mount Kenya University (MKU), Kenya\u003c/p\u003e\n \u003cp\u003eGeneral Kago Road, Thika, Kiambu, Kenya\u003c/p\u003e\n \u003cp\u003eWebsite: \u0026nbsp;\u003ca href=\"https://www.mku.ac.ke\"\u003ehttps://www.mku.ac.ke\u003c/a\u003e\u003c/p\u003e\n \u003cp\u003eInstitute of Developing Economies-Japan External Trade Organization (IDE-JETRO), Japan\u003c/p\u003e\n \u003cp\u003e3-2-2 Wakaba, Mihamaku, Chiba City, Chiba 2618545, Japan\u003c/p\u003e\n \u003cp\u003eTEL: +81-43-299-9500\u003c/p\u003e\n \u003cp\u003eWebsite: https://www.ide.go.jp/\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.11580594679186%\" valign=\"top\"\u003e\n \u003cp\u003eRole of sponsor {5c}\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"65.88419405320813%\" valign=\"top\"\u003e\n \u003cp\u003eOUC\u0026nbsp;supports\u0026nbsp;project management oversight, trial management, data management, statistical analysis, and research governance. MKU also holds overall authority together with project management and analysis.\u0026nbsp;IDE-JETRO manages the KDDI Foundation\u0026rsquo;s research fund.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Introduction","content":"\n\u003ch3\u003eBackground and rationale {6a}\u003c/h3\u003e\n\u003cp\u003eSince around 2000, significant efforts have been made in combating malaria globally, particularly in Sub-Saharan Africa, where the disease burden is exceptionally high. Various programs have been put into practice to distribute long-lasting insecticide-treated bed nets (LLINs), implement indoor residuals spraying (IRS), promote the use of rapid diagnostic testing (RDT), and provide artemisinin-based combination therapy in the most endemic areas. Along with these efforts, global malaria control made substantial progress, reducing malaria deaths by one-third between 2000 and 2019, for example (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). However, recent years have seen this progress stall, with increased cases driven by complex factors, including disrupted service provision during the COVID-19 pandemic, insecticide and drug resistance, and funding shortfalls, among many others (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Sustained and effective efforts are therefore considered crucial for continued progress in malaria elimination.\u003c/p\u003e \u003cp\u003eOur study site is Homa Bay County in western Kenya, where malaria remains a critical public health challenge. Through our fieldwork, we have observed the roles played by the supply-side efforts such as those mentioned above. At the same time, we have identified potential socio-economic constraints that may pose significant barriers to effective malaria prevention and treatment by residents, who are the consumers of health care services. Such demand-side factors, including access to and knowledge of essential tools and services, can heavily influence health-seeking behavior and adherence to recommended strategies. For example, the economic literature has pointed out that people spend more for treatment than for prevention (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Also, the prevention of infectious diseases such as malaria by one individual can reduce the risks of other individuals nearby, a property called a positive externality. In this case, people may be discouraged from taking preventive measures if they expect others to do so as well. This phenomenon, known as \"free-riding,\" can undermine overall disease control efforts (\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur team conducted an experimental intervention aimed at addressing these demand-side constraints (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). We targeted two crucial factors affecting the people\u0026rsquo;s demand: knowledge and cost of malaria prevention and early treatment. Employing a cluster randomized controlled trial (cRCT) design, we compared a conditional cash transfer (CCT) arm and a lottery incentive scheme (LIS) arm to a control group. The financial incentives were linked to malaria testing results and healthcare utilization (e.g., early treatment-seeking for suspected malaria cases). The intervention targeted households in 92 clusters in Suba South Sub-county, Homa Bay County. While the study indicated potential benefits, certain limitations necessitate a second-round intervention to refine our understanding of the intervention\u0026rsquo;s effectiveness.\u003c/p\u003e \u003cp\u003eOur second-round intervention tackles a major challenge that hindered our first-round experiment. That is, the study's setting had a relatively low baseline malaria prevalence, limiting the minimum detectable effect size. Recognizing the significance of our research, we have secured additional funding to address these limitations. The second-round intervention will not only address prior limitations but also further explore crucial aspects of the demand-side approach to malaria control. Specifically, it will help identify the roles that knowledge and cost of malaria prevention play in household behaviors and practical challenges for effectively implementing and scaling the proposed program.\u003c/p\u003e \u003cp\u003eIn addition, preliminary analysis from the first-round intervention revealed that while the educational materials successfully increased bed net usage, this did not translate to a significant reduction in malaria prevalence. We hypothesize that this may be due to the already high baseline bed net usage rate in the region, suggesting that proper net usage and adherence to other preventive measures may require additional emphasis. These observations have motivated us to revise and update the educational materials for the second-round intervention to include not only messages promoting bed net use but also advice on their best practices and other supportive preventive measures.\u003c/p\u003e \u003cp\u003eFurthermore, given the potential for substantial indirect effects of the intervention (i.e., spillover effects within households and clusters), we have increased the proportion of intervention households within each intervention cluster. This change aims to enhance our ability to gain a more comprehensive understanding of the intervention's overall impact.\u003c/p\u003e\n\u003ch3\u003eObjectives {7}\u003c/h3\u003e\n\u003cp\u003eThe primary objective is to evaluate the causal impact of the financial incentive intervention on malaria prevalence in children aged zero to 15 and all age groups during 3- and 6-month follow-up periods. The secondary objectives during a 6-month follow-up period are\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTo measure the impact of the financial incentive intervention on malaria preventive behaviors, especially bed net usage,\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTo measure the impact on malaria knowledge, and\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTo measure the spill-over effects from those exposed to the intervention to their geographic neighbors and those who are socially connected.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e\n\u003ch3\u003eTrial design {8}\u003c/h3\u003e\n\u003cp\u003eThe study is the second round of a cRCT building upon a previous experiment (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). The first-round cRCT, conducted in Suba South Sub-county, Homa Bay, Kenya, employed a two-stage randomized design. In the first stage, clusters were randomly assigned to one of three arms: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) CCT plus malaria education (EDU); (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) LIS plus EDU; or (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) a control group with no intervention. Each cluster consisted of 20 adjacent households based on household location information obtained from a census survey conducted prior to the first round of the experiment, from May to July 2021. The second stage of randomization occurred at the household level within intervention clusters to measure spillover effects. This second-round intervention will retain the same cRCT design and sample size, targeting the same clusters. However, treatment assignment will be re-randomized.\u003c/p\u003e \u003cp\u003eFor the second-round trial, we stratify clusters based on two factors: (a) baseline malaria prevalence among children under 15 years of age (as measured in the first-round baseline survey) and (b) their arm assignment in the first-round randomization. Clusters within each of these strata will then be randomly assigned to one of the three study arms (CCT, LIS, or control) using computer-generated random numbers. Figure\u0026nbsp;1 illustrates the locations and arm assignments of clusters for both the first and second rounds. Notably, the second-round stratification differs from the first round by including prior arm assignment and excluding the number of children under 15 as a stratification factor (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSimilar to the first round, the second-round intervention will employ a second stage of randomization at the household level within each intervention cluster (CCT or LIS). This will determine which households receive the treatment, allowing for the measurement of intra-cluster spillover effects. During a site visit, a household representative will draw a scratch card with a number from 1 to 10. Households drawing numbers 1\u0026ndash;8 will receive the intervention, consisting of EDU and eligibility for either the CCT or LIS incentive, depending on their cluster's assigned arm. Households drawing 9 or 10 will not receive the intervention and will serve as intra-cluster controls.\u003c/p\u003e \u003cp\u003eThe power analysis of this experiment combines the effect estimates from the first- and second-round experiments, each of which is closely related but conceptually independent. That is, each experiment provides a treatment effect estimate given the size of the expected intervention effect and the two-step randomization design, following the newly developed regression models employing a random saturation experiment (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The two intervention arms, CCT and LIS, are randomly assigned to 32 clusters, respectively, while the control arm is assigned to 28 clusters. This overall structure of the experiment forms a two-stage randomized control trial. The two estimates from two randomization samples drawn from the same population are then synthesized to one parameter estimate using a meta-analysis approach.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Methods: Participants, interventions, and outcomes","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStudy setting {9}\u003c/h2\u003e \u003cp\u003eThe study will be conducted in Suba South Sub-County, Homa Bay County, Kenya. As of the 2019 national census, the sub-county had a population of 122,383 in 27,635 households, primarily composed of the Luo and Suba ethnic groups (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). The primary occupations are fishing and farming. Housing typically consists of multiple structures, with mud walls and metal sheet roofs being the most common, although iron sheets, concrete, or stone construction can also be found (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Lake Victoria region generally experiences two rainy seasons annually: a long rainy season from March to June and a shorter one from August to October, although recent years have seen irregular patterns. Malaria incidence peaks one to two months after these rainy periods, with \u003cem\u003eAnopheles (An.) gambiae\u003c/em\u003e s.s., \u003cem\u003eAn. arabiensis\u003c/em\u003e, and \u003cem\u003eAn. funestus\u003c/em\u003e being the primary vectors (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSuba South Sub-County is served by 30 public health facilities, including two Sub-county hospitals, eight health centers, and 20 dispensaries. The sub-county is divided into community health units, each monitored by a community health promoter (CHP) responsible for malaria case detection and treatment using RDTs and ACTs, respectively. The government periodically distributes LLINs free of charge, with the most recent distribution completed in 2023/2024.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEligibility criteria {10}\u003c/h3\u003e\n\u003cp\u003eEligibility for the second-round intervention will be based on participation in the first-round experiment (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). All households that participated in the first-round baseline survey and provided consent for the follow-up surveys will be eligible for inclusion in the second round, regardless of their experimental arms in the original study. For detailed inclusion and exclusion criteria, please refer to our previous protocol (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) and Table\u0026nbsp;1 below.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInclusion and exclusion criteria for the intervention and prospective cohort survey\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInclusion criteria\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExclusion criteria\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eFirst-round Baseline (survey)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAt least one permanent resident aged 18 years or older in the household\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformed consent provided by at least one adult in the household\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBaseline (blood sampling)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMembers residing in the households participated in the baseline survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere chronic illnesses\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformed consent provided by the parent or guardian before each survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSecond-round financial incentive intervention\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold members residing in the households participated in the baseline survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformed consent provided by at least one adult in the household\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSecond-round follow-up 1 (survey)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHouseholds participated in the baseline survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformed consent provided by at least one adult in the household\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSecond-round follow-up 1 (blood sampling)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold members residing in the households participated in the baseline survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere chronic illnesses\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformed consent provided by the parent or guardian before each survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSecond-round follow-up 2 (survey)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHouseholds participated in the baseline survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformed consent provided by at least one adult in the household\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSecond-round follow-up 2 (blood sampling)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHousehold members residing in the households participated in the baseline survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere chronic illnesses\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformed consent provided by the parent or guardian before each survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eWho will take informed consent? {26a}\u003c/h3\u003e\n\u003cp\u003e Written informed consent will be obtained by trained study team members who are fluent in Luo (a local language), Swahili, and English, and have a thorough understanding of the study protocol. After confirming eligibility, these team members will present potential participants with a comprehensive information sheet detailing the study\u0026rsquo;s purpose and contents as well as their right to withdraw at any time. The information sheet will be available in both Luo and English. For participants who are unable to read, the information will be conveyed verbally by a study team member. Participants will be given ample opportunity to ask questions and discuss any concerns before being asked to provide their consent. Written consent will be obtained only after the participant demonstrates a clear understanding of the study and voluntarily agrees to participate.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAdditional consent provisions for collection and use of participant data and biological specimens {26b}\u003c/h2\u003e \u003cp\u003eIn addition to the study overview, the study information sheet will provide detailed information regarding the collection, storage, and use of personal data and biological specimens obtained during baseline and follow-up surveys, as well as blood sampling procedures.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eInterventions\u003c/h2\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eExplanation for the choice of comparators {6b}\u003c/h2\u003e \u003cp\u003eLLINs are the most widely used malaria preventive measure in Kenya. The Kenya National Malaria Control Programme coordinates free LLIN distribution every three years, and county governments are responsible for delivery to residents in endemic areas. As all target households in this trial will have unrestricted access to LLINs through this program, the control group will reflect the current standard of prevention and care in the region.\u003c/p\u003e \u003cp\u003eThe primary purpose of this trial is to evaluate the incremental effect of financial incentives combined with malaria education on top of existing LLIN coverage and usual care practices. Therefore, the control group households are expected to engage in standard malaria prevention and treatment-seeking behaviors, including LLIN use, as dictated by the national program and individual choices.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eIntervention description {11a}\u003c/h2\u003e \u003cp\u003eOur survey teams will visit households in all target clusters. For households in the control clusters, the teams will explain the upcoming follow-up survey at three and six months, confirm continued study participation, and conduct a short interview. In the intervention clusters, the team will also explain the follow-up surveys and confirm participation, but additionally inform households that they are part of a pilot intervention. They will then explain that eligibility for the intervention will be determined by a scratch card draw, with numbers 1\u0026ndash;8 qualifying for the intervention (malaria education and a financial incentive) and numbers 9\u0026ndash;10 not. The survey team will ensure the household representative understands the incentive scheme before the draw and will re-explain if necessary. For households selected for the intervention through the scratch card draw, the survey team will explain the specific reward scheme and the timing of the follow-up surveys at three and six months, and their members are invited to watch the malaria education material on a tablet device and then proceed to a short interview. Households unselected for the intervention will be informed that they will not receive the intervention and proceed to a short interview only. The detailed instruction script for enumerators throughout this intervention process is provided in Appendices 1 and 2.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCriteria for discontinuing or modifying allocated interventions {11b}\u003c/h2\u003e \u003cp\u003eGiven the low-risk nature of the financial incentive intervention and the absence of anticipated direct health risks, discontinuation of the intervention for individual participants will primarily occur under two circumstances. They include participant request (when a participant explicitly requests to withdraw from the study) and loss to follow-up (when a participant is lost to follow-up, including migration). Crossover from the control arm to the intervention arm will not be permitted during the follow-up period. Participants who migrate between study arms or emigrate from the study areas will be dropped from the study follow-up.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStrategies to improve adherence to interventions {11c}\u003c/h2\u003e \u003cp\u003eIn this study, adherence refers to the continued participation of individuals from both intervention-eligible and intervention-ineligible households throughout the follow-up period. Adherence will be monitored during the follow-up surveys by confirming the presence of participants and collecting the required blood samples.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eRelevant concomitant care permitted or prohibited during the trial {11d}\u003c/h2\u003e \u003cp\u003eThere are no restrictions on concomitant care during the trial. All study participants, regardless of their assigned arm, are permitted to continue their usual healthcare practices, including the use of freely distributed LLINs and access to standard malaria testing and care through both public and private healthcare providers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eProvisions for post-trial care {30}\u003c/h2\u003e \u003cp\u003eAll study participants will remain under the standard care of the existing health system in Homa Bay County throughout and after the trial. Given the low-risk nature of the intervention, no specific post-trial care is anticipated to be necessary beyond the usual medical services available in the community.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eOutcomes {12}\u003c/h2\u003e \u003cp\u003eThe primary outcomes of the study are (i) malaria prevalence by PCR in children and adults at three and six months post-intervention, (ii) change in the use of LLIN at three and six months post-intervention, and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) change in malaria knowledge and perception among community residents at three and six months post-intervention. The secondary outcome is malaria prevalence by RDT in children and adults at three and six months post-intervention.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eParticipant timeline {13}\u003c/h2\u003e \u003cp\u003eThis study is the second round of a cRCT evaluating the impact of educational and financial incentives on malaria prevention and treatment behaviors (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). The first round of the study included the recruitment of participants and the collection of baseline data. As such, no additional recruitment is planned for this second round. Instead, the existing cohort of participants will be re-randomized into intervention and control arms to assess the effectiveness of a refined intervention. This sequential approach allows us to build upon the existing data and infrastructure, maximizing efficiency and minimizing disruption to the community.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStudy timeline\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eSTUDY PERIOD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEnrolment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAllocation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003ePost-allocation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eClose-out\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTIMEPOINT (month)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003e-19\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003e3\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003e6\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e18\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eENROLMENT\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEligibility screen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformed consent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAllocation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eINTERVENTIONS\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u0026thinsp;+\u0026thinsp;Incentivization (CCT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u0026thinsp;+\u0026thinsp;Incentivization (LIS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eASSESSMENTS\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuestionnaire survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eX\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCapillary blood sampling by lab tech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eSample size {14}\u003c/h2\u003e \u003cp\u003eBased on an independent survey conducted concurrently in our study area, the estimated malaria RDT positivity rate is approximately 30%. With an average household size of 5 (as per our census data), we aim to detect a combined direct and spillover effect of our intervention, resulting in a 19.6% (or 5.89 percentage-point, ppt) reduction in RDT positivity for directly treated individuals and a 21.0% (or 6.30 ppt) reduction for untreated individuals within intervention clusters.\u003c/p\u003e \u003cp\u003eWe retain the same cluster definitions and sample size as the first-round intervention (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), totalling 9,200 individuals from 1,840 households grouped into 92 clusters. With no results from the previous study yet available, the sample size and treatment assignment probabilities are calculated ex-ante. To achieve sufficient statistical power to detect the aimed effect sizes, we require a 27.32% RDT positivity reduction (or 8.20 ppt) for directly treated individuals and a 31.49% reduction (or 9.45 ppt) for untreated individuals within intervention clusters. Our calculation based on the optimal saturation design (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) assumes a power of 0.8, a two-sided type-I error of 5%, a cluster size of 20 households, and an intra-cluster correlation coefficient of 0.05. This calculation results in 28 clusters randomly assigned to the control condition and 32 clusters to each intervention condition (CCT and LIS). Within each intervention cluster,16 households are expected to receive the treatment, while the remaining four will serve as untreated controls. The two intervention arms will be compared to the control arm to assess their relative effectiveness.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eRecruitment {15}\u003c/h2\u003e \u003cp\u003eNo new participants will be recruited for this second-round intervention. All households participating in the first-round study will be included in the second round, provided that they meet the continued eligibility criteria. For details on the initial recruitment, community sensitization, and census procedures, please refer to our previous protocol (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eAssignment of interventions: allocation\u003c/h2\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003eSequence generation {16a}\u003c/h2\u003e \u003cp\u003eA new set of random numbers, independent of those generated in the first round, will be generated in the for each cluster using the statistical software R. These numbers will follow a uniform distribution between 0 and 1 with the seed set to the date of randomization in \u0026lsquo;\u003cem\u003eyyyymmdd\u003c/em\u003e\u0026rsquo; format (e.g., 20240321 for March 21st, 2024). R\u0026rsquo;s built-in functions set.seed() and runif() will be used for this procedure.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eConcealment mechanism {16b}\u003c/h2\u003e \u003cp\u003eFollowing stratification based on the malaria prevalence among children under 15 and the first-round intervention arm, a random number will be assigned to each cluster. The stratification creates six strata (2 x 3). Within each stratum, clusters will be sorted in ascending order based on their assigned random numbers. The clusters with the lowest random numbers (four to five per stratum) will be assigned to the control arm, followed by the CCT arm (five to six per stratum), and finally the LIS arm (five to six per stratum). This will result in a total of 28 control clusters, 32 CCT clusters, and 32 LIS clusters.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eImplementation {16c}\u003c/h2\u003e \u003cp\u003eA designated team member will generate the cluster-level allocation sequence on the day the intervention begins. Local study assistants will enroll participants and implement the assigned interventions in the respective clusters.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eAssignment of interventions: Blinding\u003c/h2\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eWho will be blinded {17a}\u003c/h2\u003e \u003cp\u003eCluster-level arm assignment will not be disclosed to trial participants. However, due to social interactions, participants may become aware of different arm assignments across clusters. We will assess the extent of this information flow through surveys.\u003c/p\u003e \u003cp\u003eWithin intervention arms (CCT and LIS), household representatives will be aware of their household\u0026rsquo;s treatment status due to the lottery scratch card randomization.\u003c/p\u003e \u003cp\u003eStudy team members participating in field activities cannot be blinded due to their involvement in cluster and household randomization. However, laboratory- and office-based personnel (e.g., microscopists and laboratory technicians) will remain blinded to participant identity and intervention status, as biological specimens will be identified by unique numeric study identifiers, and personal information will be removed before analyses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eProcedure for unblinding if needed {17b}\u003c/h2\u003e \u003cp\u003eAs this is a low-risk socio-economic intervention with no anticipated physical risks to participants, the need for unblinding procedures is currently not foreseen.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eData collection and management\u003c/h2\u003e \u003cdiv id=\"Sec28\" class=\"Section4\"\u003e \u003ch2\u003ePlans for assessment and collection of outcomes {18a}\u003c/h2\u003e \u003cp\u003eMalaria prevalence will be estimated using cross-sectional malariometric surveys. The baseline survey was conducted at the beginning of the first-round study, and two follow-up surveys for the second-round experiment will be conducted approximately three and six months post-intervention. Malaria status will be determined using RDT, microscopy, and PCR, following the same procedures as described in the first-round protocol (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMalaria incidence will be assessed at both three- and six-month follow-up surveys, using the same procedure as described in the first-round protocol (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). During household visits, enumerators will administer a structured questionnaire to each participating household, collecting data on any history of fever, malaria episodes, or visits to local health facilities within the previous three months (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEnumerators and certified medical laboratory staff will be trained on the questionnaire's content and the use of the CSPro application data collection, adhering to the same procedures outlined in our first protocol (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). This includes built-in validation and completion checks to ensure data quality and completeness. To avoid duplication, all sample collection materials, such as microscope slides, filter papers, and sample tubes, will be pre-labeled with auto-generated serial numbers. The CSPro application will prompt staff to confirm participant identity and serial number before blood sampling, and the completeness of sampling will be verified twice: in the field and at the laboratory.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003ePlans to promote participant retention and complete follow-up {18b}\u003c/h2\u003e \u003cp\u003eWe will employ the same participant retention and follow-up strategies that proved successful in our first-round intervention (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Specifically, our survey team will schedule household visits in advance, confirming the date and time with participants at least one week prior. CHPs will report any participant concerns or issues to the research team, and collaborative discussions will be held to address these issues promptly. Additionally, the research team will periodically accompany enumerators during household visits to reinforce the importance of the study and maintain participant engagement.\u003c/p\u003e \u003cp\u003eTo enhance participant retention, we will implement a multi-faceted approach incorporating culturally tailored strategies, reflecting our established relationship with the community. This will include regular SMS and phone call reminders to participants, as well as personalized home visits by CHPs. These CHPs will serve as a trusted point of contact, addressing any questions or concerns participants may have and reinforcing the importance of their continued participation.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData management {19}\u003c/h3\u003e\n\u003cp\u003eData management for this second-round intervention will largely follow the established procedures from the first round, as detailed in our previous protocol (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Data will be collected on Android-based tablets using the CSPro application, incorporating built-in data validation checks. Follow-up survey data will be uploaded to the CSPro server, and after quality verification by data managers, local data will be deleted from the tablets to prevent overwriting. Each visit will be pre-programmed within CSpro for streamlined data entry. Specially trained enumerators who are locally hired and familiar with the participants will conduct the interviews, verifying participant identity before data entry. Data managers will perform periodic data quality checks on the server. Access to the survey data will be restricted to the study\u0026rsquo;s data analysts and managers.\u003c/p\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003eConfidentiality {27}\u003c/h2\u003e \u003cp\u003eTo maintain confidentiality, each study participant is assigned a unique identifier. Personally identifiable information unnecessary for data analysis will be removed. The anonymized data will be stored separately from the key linking personal information on a secure server accessible only to authorized research staff. While publications will primarily contain aggregated data, anonymized individual-level data may also be included to enhance transparency and reproducibility, ensuring that no personally identifiable information can be derived from the published information.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePlans for collection, laboratory evaluation and storage of biological specimens for genetic or molecular analysis in this trial/future use {33}\u003c/b\u003e \u003c/p\u003e \u003cp\u003eBlood samples will be collected to examine malaria infection status using multiple methods, characterize immune responses to malaria parasites and mosquito saliva, and conduct malaria parasite genomic analyses. No human genetic studies are planned for this study. However, any remaining biological specimens after these analyses will be stored indefinitely for future research purposes unless the participants explicitly opt out during the informed consent process. Participants are provided with the study team\u0026rsquo;s contact information in the consent form and may withdraw from this study or any future research using their samples at any time without penalty or loss of benefits.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec32\" class=\"Section2\"\u003e \u003ch2\u003eStatistical methods\u003c/h2\u003e \u003cdiv id=\"Sec33\" class=\"Section3\"\u003e \u003ch2\u003eStatistical methods for primary and secondary outcomes {20a}\u003c/h2\u003e \u003cp\u003eThe intention-to-treat (ITT) analysis will be the primary approach for both the primary and secondary outcomes. The impact of the intervention on these outcomes will be assessed using the regression framework as proposed by the prior study for a two-stage cRCT (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). This analysis will allow us to estimate the ITT effects, both direct and spillover, on treated and untreated households within a cluster while controlling for potential confounders such as age, gender, house structure, and socioeconomic indicators. A similar regression approach will be employed for the analysis of secondary outcomes. As a supplementary analysis, we plan to conduct and a per-protocol analysis, which will include only those participants who adhere to the study protocol and complete all required follow-up assessments. This analysis will provide additional insights into the intervention\u0026rsquo;s effect under ideal conditions of full compliance.\u003c/p\u003e \u003cp\u003eIn addition to the primary and secondary analyses for the second-round intervention, we plan to conduct a combined analysis of the data from both the first and second rounds. This analysis will leverage Bayesian updating techniques to integrate the findings from both studies and obtain a more precise and comprehensive estimate of the intervention.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec34\" class=\"Section3\"\u003e \u003ch2\u003eInterim analyses {21b}\u003c/h2\u003e \u003cp\u003eWe do not plan an interim analysis.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eMethods for additional analyses (e.g., subgroup analyses) {20b}\u003c/h3\u003e\n\u003cp\u003eGiven the known association between malaria risk and socioeconomic factors (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), we plan to conduct subgroup analyses to explore potential heterogeneity in the intervention\u0026rsquo;s effects across different socioeconomic backgrounds. These analyses will utilize relevant socioeconomic indicators collected during the baseline survey. The same regression model employed for the primary analysis (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) will be used to estimate treatment effects within each subgroup. If feasible, we intend to assess the interaction between the intervention and socioeconomic variables to formally test whether the intervention\u0026rsquo;s effect differs across subgroups defined by socioeconomic variables.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMethods in analysis to handle protocol non-adherence and any statistical methods to handle missing data {20c}\u003c/b\u003e \u003c/p\u003e \u003cp\u003eOnce all data collection is completed, the extent and patterns of missing data will be assessed. If necessary, multiple imputation methods may be used to handle missing data.\u003c/p\u003e\n\u003ch3\u003ePlans to give access to the full protocol, participant-level data and statistical code {31c}\u003c/h3\u003e\n\u003cp\u003eThis manuscript is the full protocol. The authors will create anonymized datasets. Future statistical codes will be made available upon reasonable request.\u003c/p\u003e \u003cdiv id=\"Sec37\" class=\"Section2\"\u003e \u003ch2\u003eOversight and monitoring\u003c/h2\u003e \u003cdiv id=\"Sec38\" class=\"Section3\"\u003e \u003ch2\u003eComposition of the coordinating centre and trial steering committee {5d}\u003c/h2\u003e \u003cp\u003eA coordinating centre has been established to oversee the trial's day-to-day operations. This centre includes a communication group comprising enumerators and laboratory technicians, who exchange experiences and address operational challenges. A local management team, consisting of study investigators from Kenya and Japan, provides guidance and ensures sample and data integrity. A steering committee, composed of key researchers from Kenya and Japan, including the principal investigator (PI) and co-PI, will convene monthly meetings to monitor overall trial progress and make strategic decisions.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec39\" class=\"Section2\"\u003e \u003ch2\u003eComposition of the data monitoring committee, its role and reporting structure {21a}\u003c/h2\u003e \u003cp\u003eGiven the low-risk nature of the intervention, a formal data monitoring committee has not been established for this study. However, to ensure data quality and methodological rigor, the research team will consult with an independent statistician as needed for additional review and validation of statistical analyses.\u003c/p\u003e \u003cdiv id=\"Sec40\" class=\"Section3\"\u003e \u003ch2\u003eAdverse event reporting and harms {22}\u003c/h2\u003e \u003cp\u003eThe financial incentives and malaria education are not expected to pose significant risks. However, should any adverse events occur during the study period, participants will be instructed to report to their designated CHP, who will then promptly inform the research team and Homa Bay County Ministry of Health (MOH). MOH\u0026rsquo;s medical officers will assess the relatedness of each reported event. In the event of a serious adverse event suspected to be study-related, the PI will be immediately notified, and the study team, in consultation with the MOH and Homa Bay County Teaching and Referral Hospital representatives, will convene an urgent meeting to review the case and determine its relatedness to the study. Appropriate action, such as protocol modifications, additional medical care, or study termination, will be taken if the case is deemed related to the study and considered to do excessively more harm than good to participants and communities.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eFrequency and plans for auditing trial conduct {23}\u003c/h3\u003e\n\u003cp\u003eRegular monitoring will occur throughout the study to ensure adherence to the protocol and data quality. This can include a pre-implementation review of all study procedures, monthly progress meetings during follow-up, annual reports and renewal applications to the relevant IRBs (Otaru University of Commerce, Japan, and Mount Kenya University, Kenya), and regular data quality checks.\u003c/p\u003e\n\u003ch3\u003ePlans for communicating important protocol amendments to relevant parties (e.g., trial participants, ethical committees) {25}\u003c/h3\u003e\n\u003cp\u003eAny substantial protocol modifications that may impact the study\u0026rsquo;s conduct, potential benefits or harm to participants, or participant safety will be submitted to the relevant institutional review boards (IRBs) at Mount Kenya University and Otaru University of Commerce for approval prior to implementation. Upon approval, such amendments will be communicated to study participants and updated in the trial registry. Minor amendments not impacting participant safety or study validity will be documented and reported to the IRBs.\u003c/p\u003e \u003cp\u003e \u003cb\u003eDissemination plans {31a}\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe results of this study will be shared with relevant stakeholders, including the Homa Bay County Government and Kenya National Malaria Control Program, to discuss the potential for scaling up the intervention. Findings will also be disseminated through peer-reviewed publications and presentations at scientific conferences, with the aim of informing the development of novel malaria control strategies in other malaria-endemic regions. Furthermore, feedback from research participants will be actively sought and incorporated into future refinements of the intervention, ensuring its continued relevance and acceptability within the community.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eDespite significant progress in global malaria reduction since 2000, recent years have witnessed a stagnation in this decline, with cases even increasing in certain regions (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). This trend is particularly concerning in high-burden areas such as Suba South Sub-county in Homa Bay County, Kenya, where malaria remains a persistent public health challenge. While past efforts have focused largely on increasing the availability of malaria prevention and treatment tools, our research seeks to investigate the impact of addressing demand-side barriers to their uptake and utilization. Although our previous experimental study provided a promising framework for an educative and incentivized intervention to improve malaria prevention and treatment behaviors, limitations in sample size and baseline malaria prevalence hindered our ability to draw definitive conclusions. Therefore, this second-round intervention thus seeks to address these shortcomings, aiming to provide a more robust assessment of the impact of parental education and financial incentives on children's malaria control within this specific context.\u003c/p\u003e \u003cp\u003eWe propose a second-round cRCT experiment to investigate the impact of demand-side interventions on malaria control. We aim to expand upon our prior research, which examined the effectiveness of combined educational and incentive-based interventions in promoting malaria prevention among young children. Mirroring the initial study, the second-round intervention will retain the cluster-randomized design and sample size, targeting the same 92 clusters within Suba South Sub-county. The educational materials will be enhanced by incorporating practical guidance on malaria prevention, such as bed net maintenance, addressing a gap identified in our previous work. We will also continue to investigate the effectiveness of the financial incentive schemes (CCTs and LIS), adjusting reward amounts to 300 KSh (CCT) and 3,000 KSh (10% chance of winning for LIS) to align with current treatment costs and local inflation rates. The program's effect will be assessed not only within this second-round cRCT but also through a combined analysis with the first-round intervention, yielding a more comprehensive understanding of the overall experimental impact, which will in part address one of the limitations of the first-round intervention that a tight sample size and the low baseline prevalence lowered our statistical power to detect the true program effect. The goal of this approach is to increase uptake of preventive measures and early treatment through optimized incentives, thereby reducing the overall burden of malaria.\u003c/p\u003e \u003cp\u003eThis second-round intervention has the potential to significantly inform malaria control policies and programs. By generating robust evidence on the effectiveness of demand-side interventions, particularly educational and incentive-based strategies, our research can guide the development of scalable, practical solutions for malaria elimination. The insights gained will contribute to a growing body of evidence-based approaches, ultimately impacting the lives of countless individuals at risk of this devastating disease.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTrial status\u003c/b\u003e \u003c/p\u003e \u003cp\u003eRecruitment of the current second-round intervention is based on the first-round trial which started on January 7, 2022, and the final subject enrolment was completed on March 8, 2022 (see also Table\u0026nbsp;3). The second-round intervention plans two follow-up surveys. The first is planned to take place through May and July 2024, and the second through August and October 2024. The progress of the first-round intervention is also listed for transparency purposes. The first-round intervention started on June 18, 2022, and ended on July 29, 2022. The first-round follow-up survey started on December 19, 2022, and ended on February 10, 2023. The current protocol is version 1.0 of May 26, 2024.\u003c/p\u003e \u003cp\u003eThis study represents the second round of a cRCT building upon the previous experiment (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Since participant recruitment was completed during the first round, it was not possible to submit this protocol manuscript before recruitment completion. However, this submission occurs before the post-allocation follow-up surveys, aligning with the journal's criteria of submission before the last patient/last visit. Importantly, this second round trial aims to address a limitation of the first round, namely the unexpectedly low statistical power due to the lower-than-anticipated baseline malaria prevalence, by re-randomization and collection of additional data to provide a more robust assessment of the intervention\u0026rsquo;s effectiveness. By addressing the limitations of the first round and strengthening the evidence base for demand-side interventions, this study will inform the development of more effective malaria control policies and programs, ultimately benefiting both the scientific community and the populations most affected by this disease. For details on the study timeline, please refer to Fig.\u0026nbsp;2 (Study flowchart and sampling timeline) and Tables\u0026nbsp;2 (Study timeline) and 3 (Trial status and plan).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTrial status and plan\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAction\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe date of the first enrolment (baseline)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJanuary 7, 2022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFinalize the enrolment (baseline)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarch 8, 2022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStart the first-round intervention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJune 18, 2022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplete the first-round intervention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJuly 29, 2022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStart the first-round follow-up survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDecember 19, 2022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplete the first-round follow-up survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFebruary 10, 2023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStart the second-round intervention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJanuary 14, 2024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplete the second-round intervention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFebruary 23, 2024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStart the second-round follow-up survey 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMay 27, 2024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplete the second-round follow-up survey 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJuly 2024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStart the second-round follow-up survey 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAugust 2024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplete the second-round follow-up survey 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOctober 2024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLLIN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elong-lasting insecticide-treated net\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePBO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epiperonyl butoxide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eITN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInsecticide-treated net\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRDT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003erapid diagnostic test\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eACT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eartemisinin combination therapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCHP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecommunity health promoter\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCCT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econditional cash transfer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLIS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elottery incentive scheme\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEDU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emalaria education using the original animated tablet-based material (12)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to express our sincere gratitude to this study\u0026apos;s participants, field, and laboratory staff. We also acknowledge the collaboration and support of health offices in Homa Bay County, Kenya.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions {31b}\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAK is the principal investigator, and JG is the co-principal investigator. TM, MN, and AK developed the original\u0026nbsp;study\u0026nbsp;concept. TM, MN, WK, JK,\u0026nbsp;JO, VO,\u0026nbsp;JG, and AK\u0026nbsp;participated in\u0026nbsp;discussions\u0026nbsp;and contributed to the study protocol. TM,\u0026nbsp;MN, JO, and VO\u0026nbsp;drafted the manuscript. WK,\u0026nbsp;GO,\u0026nbsp;JK, JG, and AK\u0026nbsp;provided critical\u0026nbsp;revisions of the\u0026nbsp;manuscript.\u0026nbsp;All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding {4}\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study\u0026nbsp;received support from\u0026nbsp;the\u0026nbsp;JICA/AMED joint research project (SATREPS,\u0026nbsp;Grant\u0026nbsp;No. 20JM0110020H0002)\u0026nbsp;[to AK and JG],\u0026nbsp;JSPS KAKENHI (Grant No.\u0026nbsp;JP21H051080 and 23KK0024)\u0026nbsp;[to TM].\u0026nbsp;the KDDI Foundation (project title \u0026lsquo;E-Learning, Mobile Transfer, and Malaria Elimination\u0026rsquo;) [to MN].\u0026nbsp;The funders had\u0026nbsp;no role in the study design, data collection\u0026nbsp;and\u0026nbsp;analysis, interpretation,\u0026nbsp;the decision to publish, or the preparation of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials {29}\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study regimen, consent forms, assent forms, and study-related materials\u0026nbsp;will be\u0026nbsp;accessible from the corresponding author\u0026nbsp;upon reasonable request. The final trial dataset will be\u0026nbsp;made\u0026nbsp;available to all investigators\u0026nbsp;involved in the study.\u0026nbsp;Anonymized\u0026nbsp;datasets\u0026nbsp;and relevant analysis scripts will be published in a data repository and made\u0026nbsp;available\u0026nbsp;upon completion of the data analysis and manuscript preparation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate {24}\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is approved by the Mount Kenya University Independent Ethics and Research Committee (MKU-IERC) (approval number: MKU/ERC/2165) and the Ethics Committee at Otaru University of Commerce (approval number:\u0026nbsp;OUC-2020-07-01).\u003c/p\u003e\n\u003cp\u003eConsent will be sought from study participants before the experimental intervention is implemented. Participants have the right to withdraw from the study at any time and the option to withhold previously collected samples from any future analyses and studies.\u0026nbsp;The consent form clearly states that the samples collected in this study may potentially be used for other research purposes. In such cases, we will obtain the necessary ethical approval and allow participants to opt out.\u0026nbsp;All experiments will be carried out in adherence to WHO requirements and\u0026nbsp;the\u0026nbsp;Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication {32}\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable - no identifying images or other personal or clinical details of participants are presented here or will be presented in reports of the trial results. The participant information materials and informed consent forms are available from the corresponding author on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests {28}\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to disclose.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization. World Malaria Report 2023. Geneva: World Health Organization; 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatsumoto T, Nagashima M, Kagaya W, Kongere J, Gitaka J, Kaneko A. Evaluation of a financial incentive intervention on malaria prevalence among the residents in Lake Victoria basin, Kenya: study protocol for a cluster-randomized controlled trial. Trials. 2024;25(1):165.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDupas P, Miguel E. Chapter 1 - Impacts and Determinants of Health Levels in Low-Income Countries. In: Banerjee AV, Duflo E, editors. Handbook of Economic Field Experiments [Internet]. North-Holland; 2017. pp. 3\u0026ndash;93. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.sciencedirect.com/science/article/pii/S2214658X16300113\u003c/span\u003e\u003cspan address=\"https://www.sciencedirect.com/science/article/pii/S2214658X16300113\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCohen J, Dupas P. Free Distribution or Cost-Sharing? Evidence from a Randomized Malaria Prevention Experiment*. Q J Econ. 2010;125(1):1\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIbuka Y, Li M, Vietri J, Chapman GB, Galvani AP. Free-Riding Behavior in Vaccination Decisions: An Experimental Study. Boni MF, editor. PLoS ONE. 2014;9(1):e87164.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCorey White. Measuring Social and Externality Benefits of Influenza Vaccination. J Hum Resour. 2021;56(3):749.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaird S, Bohren JA, McIntosh C, \u0026Ouml;zler B. Optimal Design of Experiments in the Presence of Interference. Rev Econ Stat. 2018;100(5):844\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKenya National Bureau of Statistics, editor. 2019 Kenya Population and Housing Census Volume II: Distribution of Population by Administrative Units. Nairobi: Kenya National Bureau of Statistics; 2019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFutami K, Dida GO, Sonye GO, Lutiali PA, Mwania MS, Wagalla S, et al. Impacts of insecticide treated bed nets on Anopheles gambiae s.l. populations in Mbita district and Suba district, Western Kenya. Parasites Vectors. 2014;7(1):63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)\u0026mdash;A metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDegarege A, Fennie K, Degarege D, Chennupati S, Madhivanan P. Improving socioeconomic status may reduce the burden of malaria in sub Saharan Africa: A systematic review and meta-analysis. Carvalho LH, editor. PLoS ONE. 2019;14(1):e0211205.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNyqvist MB, Corno L, de Walque D, Svensson J. Incentivizing Safer Sexual Behavior. Am Economic Journal: Appl Econ. 2018;10(3):287\u0026ndash;314.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"trials","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trls","sideBox":"Learn more about [Trials](http://trialsjournal.biomedcentral.com/)","snPcode":"13063","submissionUrl":"https://www.editorialmanager.com/trls","title":"Trials","twitterHandle":"MedicalEvidence","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Malaria, malaria education, conditional cash transfer, lottery incentive scheme, Kenya, cluster-randomized controlled trial","lastPublishedDoi":"10.21203/rs.3.rs-4479731/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4479731/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Despite significant progress in global malaria reduction since 2000, driven primarily by supply-side interventions including improvements in bed nets and medication availability, recent years have seen a stagnation in this decline. In certain regions, cases have even increased (1). This trend is particularly concerning in high-burden areas such as Suba South Sub-county in Homa Bay County, Kenya, where malaria remains a persistent public health challenge. However, demand-side barriers—such as lack of knowledge of the disease and perceived costs of prevention and treatment among residents—have been relatively overlooked in control efforts. To address this gap, we conducted a cluster-randomized controlled trial (cRCT) to investigate the impact of an educational intervention and financial incentives on malaria-related behaviors (2). This second-round cRCT aims to build upon the first-round findings, with modifications to the experimental design and educational content to further explore the potential of demand-side interventions and inform future malaria control strategies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: This second-round cRCT will re-randomize the original 92 clusters to either conditional cash transfer (CCT), lottery incentive scheme (LIS), or control arms. Each intervention arm will includeupdated malaria education and financial incentives linked to negative malaria test results, with reward amounts adjusted to reflect local inflation. We will re-assess malaria prevalence using RDT, microscopy, and PCR at three and six months post-intervention. The primary outcomes are changes in malaria prevalence, LLIN usage, and knowledge/perception of malaria. The analysis will combine data from both the first and second rounds to improve statistical power and provide a more comprehensive assessment of the intervention's impact.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiscussion\u003c/strong\u003e: This study addresses the limitations of the first-round trial by increasing statistical power and refining the educational component. By evaluating the effectiveness of demand-side interventions, we aim to inform policy and program design for malaria control in high-burden settings. The resulting evidence on the role of demand-side factors will complement traditional supply-side approaches, ultimately refining future malaria control policies and programs. This research, thereby, has the potential to contribute to the development of sustainable, community-based strategies for malaria elimination.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration\u003c/strong\u003e: UMIN000053284, registered on 6th January 2024.\u003c/p\u003e","manuscriptTitle":"The Second-Round Evaluation of Financial Incentives on Malaria Prevalence in the Lake Victoria Basin, Kenya: Updated Study Protocol for a Cluster-Randomized Controlled Trial","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-17 02:31:33","doi":"10.21203/rs.3.rs-4479731/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor revision","date":"2024-10-18T04:32:59+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-07-20T16:29:14+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-18T10:15:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-09T12:09:07+00:00","index":"","fulltext":""},{"type":"submitted","content":"Trials","date":"2024-06-17T21:40:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"trials","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trls","sideBox":"Learn more about [Trials](http://trialsjournal.biomedcentral.com/)","snPcode":"13063","submissionUrl":"https://www.editorialmanager.com/trls","title":"Trials","twitterHandle":"MedicalEvidence","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"59303b73-6d47-468c-a297-e38ca374342b","owner":[],"postedDate":"August 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-27T16:25:01+00:00","versionOfRecord":{"articleIdentity":"rs-4479731","link":"https://doi.org/10.1186/s13063-025-09146-5","journal":{"identity":"trials","isVorOnly":false,"title":"Trials"},"publishedOn":"2025-10-21 16:16:59","publishedOnDateReadable":"October 21st, 2025"},"versionCreatedAt":"2024-08-17 02:31:33","video":"","vorDoi":"10.1186/s13063-025-09146-5","vorDoiUrl":"https://doi.org/10.1186/s13063-025-09146-5","workflowStages":[]},"version":"v1","identity":"rs-4479731","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4479731","identity":"rs-4479731","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}