An Adaptive Intervention Trial Design for Finding the Optimal Integrated Strategies for Malaria Control and Elimination in Africa: A Model Simulation Study

Abstract

ABSTRACT. There are a number of available and emerging malaria intervention tools that require innovative trial designs to find the optimal combinations at given epidemiologic settings. We simulated intervention strategies based on adaptive interventions, which included long-lasting insecticidal nets (LLINs), piperonyl butoxide–treated LLINs (PBO-LLINs), indoor residual spraying (IRS), and long-lasting microbial larviciding (LLML). The aims were to determine if PBO-LLINs or LLIN+IRS combination is more effective for initial interventions than LLINs and to identify the most effective intervention. We used a clustered, randomized adaptive trial design with malaria infection prevalence (MIP) as the outcome variable. The results indicate that during the initial stage of interventions, compared with regular LLINs, PBO-LLINs (relative reduction [RR]: 29.3%) and LLIN plus IRS with alternative-insecticide (RR: 26.8%) significantly reduced MIP. In the subsequent interventions, adding alternative insecticide IRS (RR: 23.8%) or LLML (RR: 31.2%) to existing PBO-LLIN was effective in further reducing MIP. During the next stage of interventions, adding LLML on top of PBO-LLIN+IRS (with alternative insecticides) had a significant impact on MIP (RR: 39.2%). However, adding IRS (with alternative insecticides) on top of PBO-LLIN+LLML did not significantly reduce MIP (11.6%). Overall, in clusters initiated with PBO-LLIN, adding LLML would be the most effective strategy in reducing MIP; in clusters initiated with LLIN+IRS, replacing LLIN+IRS with PBO-LLIN and LLML would be the most effective in reducing MIP. This study provides a new pathway for informing the optimal integrated malaria vector interventions, and the new strategy can be tested in field trials.