We will conduct malaria vector population surveillance on a monthly basis continuously till at least 8 months after the last round of larvicide application . We will monitor both indoor- and outdoor-biting mosquito abundance using CO2-baited Centers for Disease Control light traps equipped with collection bottle rotators . The collection bottle rotator, which has eight separate plastic collection bottles, will be programmed to collect active mosquitoes at 2-h intervals between 16:00–08:00. We will place two traps within each sampling compound: one inside the living room, the other outside the house 5 m away. We will conduct a total of 64 trap-nights of vector sampling per cluster per month. This will provide an estimation precision of 0.2 mosquitoes using the previously determined standard deviation. Species of collected mosquitoes will be identified and blood-feeding status will be recorded. We will test for P. falciparum sporozoite infection and blood meal source using an enzyme-linked immunosorbent assay on all specimens. For each house where the vector population was sampled, we will record the number of sleeping persons at each house on the same day as the vector survey. We will calculate sporozoite rate and EIR for each cluster. EIRs will be calculated as, and standardized to a monthly basis. The trapping method will allow for comparison of indoor- and outdoor-biting mosquito abundance and determination of nightly biting activity patterns. We will calculate indoor and outdoor transmission intensities separately assuming that all mosquitoes collected from a compound had their blood meal from the same household. We will calculate EIR for the four study periods as describe above: preintervention period: baseline vector surveillance started at least 6 months prior to the application of long-lasting microbial larvicides till intervention, intervention period, the 8-month washout period,grow trays and post intervention period: vector surveillance continued till 8 months after the last round of larvicide application.

To determine whether new malaria vector species are present in the study sites, we will sequence the ribosomal second internal transcribed spacer and mitochondrial CO1 gene in anopheline specimens that are not amplified by the recombinant deoxyribonucleic acid polymerase chain reaction method, and we will conduct phylogenetic analysis to determine whether the new species found by Stevenson et al. are also present in the study sites.We will conduct the intervention using a two-step approach. First, we will conduct a small-scale four-cluster trial to optimize the time, duration, and quantity of LLML application. Second, we will conduct a cluster randomized trial to test the effectiveness and cost effectiveness of LLML. The design has two parallel arms, i.e., control and intervention, and allows for baseline survey without intervention and crossover .We will select four clusters, two in each county, for an entomological evaluation of the optimal larvicide application scheme . We will randomly select two clusters, one in each county, treated with larvicides and the other two sites will serve as controls . We will treat temporary habitats with FourStar controlled release granule formulation, which maintains effectiveness through wet and dry periods for up to 1 month. We will treat semipermanent habitats with FourStar 90-day briquettes and permanent habitats with FourStar 180-day briquettes. Application dosage will follow the recommendation of the manufacturer, Central Life Sciences: 10 lbs per acre of water surface for the granule formulation, and one briquette per 100 ft2 of water surface for the briquette formulations, regardless of water depth. We will re-treat the habitats every 4 to 5 months. On a weekly basis in the treatment and control sites, we will use aerial samplers to determine habitat pupal productivity, and use standard dippers to determine larval abundance. This will allow for determination of habitat productivity with a tolerable error of 0.5 mosquitoes, based on the standard deviation identified in previous studies. We will monitor indoor and outdoor vector abundance using 64 trap nights per cluster per month. This sample size will allow detection of a difference in average vector abundance of 0.12 mosquitoes with 80 % statistical power and 0.05 type-I error.

We will use ELISA methods to determine Anopheles mosquitoes’ sporozoite infection and blood feeding host preference. We will analyze the data immediately after the small scale trial using analysis of variance with repeated measures and appropriate transformation to determine the effects of habitat larviciding on mosquito abundance and transmission intensity. The percentage reduction in malaria transmission intensity will be calculated.We will assign fourteen clusters each in the two counties to intervention or no intervention by a block randomization method on the basis of clinical malaria incidence, vector density, and human population size per site. Year 1 will focus on preparing the study sites and working with clinics and hospitals to help them improve their routine malaria surveillance . In year 2, we will conduct preliminary surveys on all 28 sites to determine clinical malaria incidence, vector density, geographic information system coordinates of larval habitats, and human population size. Human population size for each cluster, stratified into three age groups will be ascertained from our existing data. We will obtain age-group level aggregated morbidity data from local hospitals and clinics where the sampled residents seek treatment. We will determine vector abundance using CO2-baited CDC light traps for 16 trap-nights per cluster per month in each of the indoor and outdoor environments. Using these data, each cluster will be allocated to either treatment or control through randomization using the following procedures. First, each of the four parameters listed above will be standardized with the highest cluster as 1. Second, we will assign the highest weight for clinical malaria cases , the lowest weight for human population size , and intermediate weights for expected vector density and larval habitats , following the method of Corbel et al.. For each cluster a rank score will be computed as the sum of weighted clinical malaria incidence, vector density, habitat abundance, and human population size. Finally, the 14 clusters within each county will be sequentially numbered according to their rank scores and sorted into seven blocks of two clusters having successive rank scores.

We expect the two clusters within each block to have similar risk characteristics for clinical malaria, vector abundance, larval habitats, and human population size. In each block, the ranks of the two clusters are put into two sealed envelopes, one cluster will be randomly allocated to treatment and another to control, using computer-generated random numbers .After the larvicide application optimization and study cluster randomization, we will treat each treatment cluster with LLML at the time interval of 4 or 5 months . The first treatment will be conducted in February-March about 1 month before the beginning of the long rainy season which usually starts in April. After three treatments, we will perform no treatments for the next 8 months. This will provide useful data on the dynamics of action of the LLML and the waning efficacy of LLML over time. These data will be important in analyzing cost-effectiveness to help optimize the timing of re-treatments. After 8 months, a total washout of the LLMLs will be assumed to have taken place. Next, we will perform a crossover and switch of the control and treatment clusters. Former control clusters will receive three rounds of LLML treatment at appropriate time intervals, and the former treatment clusters will receive no LLMLs. This strategy will minimize ascertainment biases that might be attributed to care-seeking behaviors of the population or to malaria detection and reporting by malaria treatment clinics. We will test LLMLs manufactured by Central Life Sciences. The larvicide application regime is as follows: temporary, semipermanent, and permanent habitats will be treated with FourStar controlled release granule formulation, 90-day briquettes, and 180-day briquettes, respectively. Application dosage will follow the recommendation of the manufacturer: 10 lbs per acre of water surface for the granule formulation,dry racks for weed and 100 ft2 water surface per briquette. We will conduct monthly vector surveys throughout the study period to determine indoor- and outdoor-biting vector abundance, using the same sample size of 64 trap-nights per cluster per month, and sporozoite infection and mosquito blood meal analysis will be conducted on all collected specimens. To confirm larviciding efficacy, we will examine larval abundance, age structure, and pupal productivity on a monthly basis in 100 randomly selected larval habitats each from treatment and control sites using our GIS maps and data on sites where LLML was applied.Sample size was calculated based on 2010 and 2011 active case surveillance results from Iguhu and Emutete areas. Then the number of clusters required and the number of individuals required for each cluster were calculated following the methods developed by Hayes and Bennett based on cluster-randomized trials assuming equal population for each cluster. The observed malaria incidence rate was 52.7 cases per 1000 people year in 2011. We calculated the numbers of clusters and individuals required for epidemiological assessment of the long-lasting larvicide treatments to detect a 50 % protective efficacy conferred by the treatment compared with the reference group , with a power of 80 %, significance level of 5 % and the coefficient of variation of true proportions between clusters within each treatment was assumed to be 0.15.

The estimated number of clusters for the intervention will be five and the required number of individuals for each matched-pair will be 1196; assuming a design effect of 0.25 and 20 % of subjects lost to follow-up. The estimated number of clusters for the intervention will be seven and the required number of individuals for each of the matched-pairs will be fewer than 2000. The 28 clusters proposed in the randomized cluster study will detect 50 % malaria incidence reduction with 99.9 % power and 30 % incidence reduction with 85.3 % power. This is based on the current malaria incidence rate in the study sites and a two-tailed alpha with a human population size of 2000 per cluster . If the malaria incidence is 50 % lower than the current value, the design will still detect 50 % incidence reduction with 99.7 % power and 40 % reduction with 95.2 % power .We will monitor primary and secondary endpoint outcomes throughout the 5-year study period ; data analysis will be conducted in year 5. The difference in clinical malaria incidence between treatment and control groups will be compared using Poisson multivariate regression models with intervention, age, and calendar time as covariates, using a generalized estimating equations approach. GEE is necessary since incidence will be modeled monthly as a temporally-correlated repeated measure using grouped data. Intervention will be a time-varying covariate since the treatment crosses over after three intervention rounds. Since there is no intervention in the 8 months during the washout period, interval censoring will be performed to exclude the second 4 months of data during this period. The odds ratio and the 95 % confidence interval for clinical malaria rates between treatment and control groups will be calculated. Difference in vector density and EIR will be analyzed using a negative binomial regression model and the GEE approach. In all these analyses, clusters will be indicated as intervention and control, calendar time will be categorized into: pre intervention, intervention, post intervention , washout , crossover intervention, post intervention , and nonintervention, and months since intervention will also be included as an independent variable. These variables will allow for comparison between intervention and control clusters based on baseline observations, e.g., relative reduction in vector density, and allow for evaluation of cumulative effect,e.g., the second round of treatment may produce added effect following first-round treatment. Finally, for the economic evaluation, we will calculate incremental cost-effectiveness ratios based on the primary endpoint and on long-term health outcomes including malaria deaths averted. Using the “ingredients approach”, costs will be classified according to: initial setup investment , running costs , and costs of program management and quality control . Cost data will be estimated from health facility and Ministry of Health records, LLML manufacturers and financial accounts of the research project. One-way and multi-way sensitivity analysis will be undertaken to examine the implications of potential changes in variables such as larvicide price and larviciding application frequency. ICERs will be reported from both provider and societal perspectives for different transmission intensity scenarios.Larval control and environmental management have played very important roles in malaria elimination in the United States and Europe, where today larval control using biological larvicides is the primary vector control method.