Estimating spatiotemporally varying malaria reproduction numbers in a near elimination setting.
other
Where this comes from
- Record sourced from PubMed, PMID 29946060.
- Also identified by DOI 10.1038/s41467-018-04577-y and PMC identifier 6018772.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
In 2016 the World Health Organization identified 21 countries that could eliminate malaria by 2020. Monitoring progress towards this goal requires tracking ongoing transmission. Here we develop methods that estimate individual reproduction numbers and their variation through time and space. Individual reproduction numbers, R<sub>c</sub>, describe the state of transmission at a point in time and differ from mean reproduction numbers, which are averages of the number of people infected by a typical case. We assess elimination progress in El Salvador using data for confirmed cases of malaria from 2010 to 2016. Our results demonstrate that whilst the average number of secondary malaria cases was below one (0.61, 95% CI 0.55-0.65), individual reproduction numbers often exceeded one. We estimate a decline in R<sub>c</sub> between 2010 and 2016. However we also show that if importation is maintained at the same rate, the country may not achieve malaria elimination by 2020.
Medical subject headings
- Malaria