Mobile population dynamics and malaria vulnerability: a modelling study in the China-Myanmar border region of Yunnan Province, China

Infect Dis Poverty. 2018 Apr 29;7(1):36. doi: 10.1186/s40249-018-0423-6.

Abstract

Background: The China-Myanmar border region presents a great challenge in malaria elimination in China, and it is essential to understand the relationship between malaria vulnerability and population mobility in this region.

Methods: A community-based, cross-sectional survey was performed in five villages of Yingjiang county during September 2016. Finger-prick blood samples were obtained to identify asymptomatic infections, and imported cases were identified in each village (between January 2013 and September 2016). A stochastic simulation model (SSM) was used to test the relationship between population mobility and malaria vulnerability, according to the mechanisms of malaria importation.

Results: Thirty-two imported cases were identified in the five villages, with a 4-year average of 1 case/year (range: 0-5 cases/year). No parasites were detected in the 353 blood samples from 2016. The median density of malaria vulnerability was 0.012 (range: 0.000-0.033). The average proportion of mobile members of the study population was 32.56% (range: 28.38-71.95%). Most mobile individuals lived indoors at night with mosquito protection. The SSM model fit the investigated data (χ2 = 0.487, P = 0.485). The average probability of infection in the members of the population that moved to Myanmar was 0.011 (range: 0.0048-0.1585). The values for simulated vulnerability increased with greater population mobility in each village.

Conclusions: A high proportion of population mobility was associated with greater malaria vulnerability in the China-Myanmar border region. Mobile population-specific measures should be used to decrease the risk of malaria re-establishment in China.

Keywords: Importation; Individual-based model; Malaria; Mobile population; Vulnerability.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Child
  • Child, Preschool
  • China / epidemiology
  • Cross-Sectional Studies
  • Female
  • Humans
  • Infant
  • Infant, Newborn
  • Malaria / epidemiology*
  • Male
  • Middle Aged
  • Models, Theoretical
  • Myanmar
  • Population Dynamics*
  • Stochastic Processes
  • Young Adult