Determinants of MDA impact and designing MDAs towards malaria elimination

Abstract

12Malaria remains at the forefront of scientific research and global political and funding agendas. 13 Malaria models have consistently oversimplified how mass interventions are implemented. Here, 14 we present an individual based, spatially explicit model of P. falciparum malaria transmission 15 that includes all the programmatic implementation details of mass drug administration (MDA) 16 campaigns. We uncover how the impact of MDA campaigns is determined by the interaction 17 between implementation logistics, patterns of human mobility and how transmission risk is 18 distributed over space. Our results indicate that malaria elimination is only realistically 19 achievable in settings with very low prevalence and can be hindered by spatial heterogeneities in 20 risk. In highly mobile populations, accelerating MDA implementation increases likelihood of 21 elimination; if populations are more static, deploying less teams would be cost optimal. We 22 conclude that mass drug interventions can be an invaluable tool towards malaria elimination in 23 low endemicity areas, specifically when paired with effective vector control. 24 25 falciparum elimination. Our research questions are threefold: 1) what is the relevance of 71 logistical implementation details to the outcome of mass interventions? 2) How fast does target 72 coverage need to be reached for the strategy to be successful? 3) What are the key modulators of 73 malaria elimination likelihood in a short timeframe? To offer strategic guidance to national 74 malaria control programmes we also need to understand how the answers to these questions 75 hinge on key features of malaria transmission in specific areas such as artemisinin resistance 76 levels, population mobility networks, transmission heterogeneity over space, and seasonality 77 patterns. 78 79 Model Description 80 We developed a modular simulation platform that is customizable to any malaria transmission 81 setting to provide realistic outcome predictions for local and global level interventions. The 82 modules are the building blocks of an individual based, discrete time, spatially explicit, 83 stochastic model, with explicit mosquito population dynamics and human population 84 movements. We thus have villages with different mosquito densities connected by a human flow 85 network, on which different interventions are deployed at different times (Figure 1). One 86 particular innovation compared to previous published work (27-31) is the inclusion of very 87 detailed logistical processes related to intervention deployment in the field. 88 Whilst previously published models are extremely good at representing the biological processes 89 underlying malaria transmission, some even making very realistic assumptions on how coverage 90 increases over time (31), they fail to explicitly model how these interventions are carried out in 91 the field. In practice, teams of workers visit villages sequentially one by one, usually spending 4-92 6 7 days to deploy one MDA round in each village, which is quite dif...

An ingredients-based approach to costing integrated malaria elimination strategies: an example from Myanmar

“…There was no signi cant increase in any of the genetic markers for resistance after MDA [29]. The components necessary for a successful integrated malaria elimination strategy are predicted to be highly dependent on the setting [34], and Myanmar is expected to require MDA or other more intensive interventions.…”

“…Our costing model can predict the costs of a particular malaria elimination package design, but cannot make any assurances on the likelihood of success of such a package in achieving elimination elsewhere. It is designed to be used in concert with detailed knowledge of the target area and/or with mathematical models that can simulate the impact of various strategy designs on the prevalence and incidence of malaria [34].…”

Pneumococcal Competition Modulates Antibiotic Resistance in the Pre-Vaccination Era: A Modelling Study

“…This question remains a conundrum of high public health concern. Examples of such coexistence include some of the most relevant human pathogens: antiviral resistance of the immunodeficiency virus (HIV) [ 53 , 54 ], antimalarial resistance to malaria parasites [ 55 ], drug and vaccine escape by Mycobacterium tuberculosis [ 56 ], and antimicrobial resistance in Streptococcus pneumoniae [ 19 , 33 , 57 , 58 ].…”

Within-host competition modulates pneumococcal antibiotic resistance in the pre-vaccination era

“…This question remains a conundrum of high public health concern. Examples of such coexistence include some of the most relevant human pathogens: antiviral resistance of the immunodeficiency virus (HIV) [61,62] , antimalarial resistance to malaria parasites [63] , drug and vaccine escape by Mycobacterium tuberculosis [64] , and antimicrobial resistance in Streptococcus pneumoniae [34,37,41,65,66] .…”