Background Based on sensitivity analysis of the MacDonald-Ross model, it has long been argued that the best way to reduce malaria transmission is to target adult female mosquitoes with insecticides that can reduce the longevity and human-feeding frequency of vectors. However, these analyses have ignored a fundamental biological difference between mosquito adults and the immature stages that precede them: adults are highly mobile flying insects that can readily detect and avoid many intervention measures whereas mosquito eggs, larvae and pupae are confined within relatively small aquatic habitats and cannot readily escape control measures. Presentation of the hypothesis We hypothesize that the control of adult but not immature mosquitoes is compromised by their ability to avoid interventions such as excito-repellant insecticides. Testing the hypothesis We apply a simple model of intervention avoidance by mosquitoes and demonstrate that this can substantially reduce effective coverage, in terms of the proportion of the vector population that is covered, and overall impact on malaria transmission. We review historical evidence that larval control of African malaria vectors can be effective and conclude that the only limitations to the effective coverage of larval control are practical rather than fundamental. Implications of the hypothesis Larval control strategies against the vectors of malaria in sub-Saharan Africa could be highly effective, complementary to adult control interventions, and should be prioritized for further development, evaluation and implementation as an integral part of Rolling Back Malaria.

This data asset contains data from insecticide resistance tests conducted by the President's Malaria Initiative (PMI) VectorLink project using Centers for Disease Control (CDC) and Prevention bottle bioassays and World Health Organization (WHO) tube test bioassays. The standard CDC bottle bioassay and standard WHO tube test consist of exposing mosquitoes to a single insecticide to determine the percent mortality of the exposed mosquitoes at key time intervals.

This dataset includes deidentified data on patients receiving artesunate through the National Artesunate for Severe Malaria Program from April- December 2019. This dataset contains the data from the case report form only. Please see the links below for the other datasets and the attached document 'Guide to NASMP Datasets': Data from Case Report Form- https://data.cdc.gov/Global-Health/National-Artesunate-for-Severe-Malaria-Program-Cas/igaz-icki Data on Artesunate Dosing- https://data.cdc.gov/dataset/National-Artesunate-for-Severe-Malaria-Program-Art/qan4-gt4k Data on Microscopy (Parasitemia values)- https://data.cdc.gov/Global-Health/National-Artesunate-for-Severe-Malaria-Program-Mic/v2k9-ctv4 All data can be easily linked using the ParticipantID field, a unique ID number assigned to each participant.

This data asset contains data from IM advanced MDRT. IM supported the NMCP to improve the performance of laboratory technicians in malaria microscopy according to WHO guidelines through a five-day advance MDRT. This training also allowed to prepare the participants to have their best performance at External Competency Assessment for Malaria Microscopists (ECAMM). The training included building skills theory and diagnostics procedures for malaria, parasite detection (PD), species identification (ID), and parasite counting (PC), as well as slide preparation, slide staining, use of malaria rapid diagnostic tests (mRDTs), biosafety, microscope maintenance, and improvement of QA measures according to national guidelines.