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Multi-year optimization of malaria intervention: a mathematical model

Overview of attention for article published in Malaria Journal, March 2016
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1 tweeter

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Title
Multi-year optimization of malaria intervention: a mathematical model
Published in
Malaria Journal, March 2016
DOI 10.1186/s12936-016-1182-0
Pubmed ID
Authors

Harry J. Dudley, Abhishek Goenka, Cesar J. Orellana, Susan E. Martonosi

Abstract

Malaria is a mosquito-borne, lethal disease that affects millions and kills hundreds of thousands of people each year, mostly children. There is an increasing need for models of malaria control. In this paper, a model is developed for allocating malaria interventions across geographic regions and time, subject to budget constraints, with the aim of minimizing the number of person-days of malaria infection. The model considers a range of several conditions: climatic characteristics, treatment efficacy, distribution costs, and treatment coverage. An expanded susceptible-infected-recovered compartment model for the disease dynamics is coupled with an integer linear programming model for selecting the disease interventions. The model produces an intervention plan for all regions, identifying which combination of interventions, with which level of coverage, to use in each region and year in a 5-year planning horizon. Simulations using the model yield high-level, qualitative insights on optimal intervention policies: The optimal intervention policy is different when considering a 5-year time horizon than when considering only a single year, due to the effects that interventions have on the disease transmission dynamics. The vaccine intervention is rarely selected, except if its assumed cost is significantly lower than that predicted in the literature. Increasing the available budget causes the number of person-days of malaria infection to decrease linearly up to a point, after which the benefit of increased budget starts to taper. The optimal policy is highly dependent on assumptions about mosquito density, selecting different interventions for wet climates with high density than for dry climates with low density, and the interventions are found to be less effective at controlling malaria in the wet climates when attainable intervention coverage is 60 % or lower. However, when intervention coverage of 80 % is attainable, then malaria prevalence drops quickly in all geographic regions, even when factoring in the greater expense of the higher coverage against a constant budget. The model provides a qualitative decision-making tool to weigh alternatives and guide malaria eradication efforts. A one-size-fits-all campaign is found not to be cost-effective; it is better to consider geographic variations and changes in malaria transmission over time when determining intervention strategies.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 1 1%
Mexico 1 1%
United States 1 1%
Unknown 64 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 19 28%
Researcher 12 18%
Student > Ph. D. Student 10 15%
Student > Bachelor 7 10%
Student > Postgraduate 4 6%
Other 7 10%
Unknown 8 12%
Readers by discipline Count As %
Medicine and Dentistry 13 19%
Agricultural and Biological Sciences 8 12%
Economics, Econometrics and Finance 6 9%
Social Sciences 6 9%
Pharmacology, Toxicology and Pharmaceutical Science 4 6%
Other 17 25%
Unknown 13 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 March 2016.
All research outputs
#5,566,111
of 7,361,309 outputs
Outputs from Malaria Journal
#2,020
of 2,449 outputs
Outputs of similar age
#196,820
of 280,306 outputs
Outputs of similar age from Malaria Journal
#169
of 199 outputs
Altmetric has tracked 7,361,309 research outputs across all sources so far. This one is in the 13th percentile – i.e., 13% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,449 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 9th percentile – i.e., 9% of its peers scored the same or lower than it.
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We're also able to compare this research output to 199 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.