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Estimating spatiotemporally varying malaria reproduction numbers in a near elimination setting

  • Isobel Routledge
  • , José Eduardo Romero Chevéz
  • , Zulma M. Cucunubá
  • , Manuel Gomez Rodriguez
  • , Caterina Guinovart
  • , Kyle B. Gustafson
  • , Kammerle Schneider
  • , Patrick G.T. Walker
  • , Azra C. Ghani
  • , Samir Bhatt

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

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 c, 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 c 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.

Original languageEnglish
Article number2476
JournalNature Communications
Volume9
Issue number1
DOIs
StatePublished - 01 Dec 2018
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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