The relationship of malaria between Chinese side and Myanmar's five special regions along China-Myanmar border: a linear regression analysis

Malar J. 2016 Jul 18;15(1):368. doi: 10.1186/s12936-016-1413-4.

Abstract

Background: Understanding malaria along the international border of two countries is important for malaria control and elimination; however, it is difficult to investigate a quantitative relationship between two countries' border areas due to a shortage of malaria surveillance data.

Methods: A linear regression analysis was conducted to investigate the logarithmic annual parasite incidence (API), numbers of imported cases and local infections in 19 Chinese border counties, with logarithmic API and parasitic prevalence in Myanmar's five special regions.

Results: API in 19 Chinese counties was stronger correlated with parasite prevalence than with API in five special regions of Myanmar, correlation coefficient (R) 0.8322 (95 % CI 0.0636-0.9084) versus 0.9914 (95 % CI 0.9204-0.9914). Numbers of imported malaria cases and local malaria infections in 19 Chinese counties were also closer correlated with parasite prevalence than with API in five special regions of Myanmar.

Conclusions: There is a strong correlation of malaria between China's side and Myanmar's side along the international border. Parasite prevalence is a better indicator of the true malaria situation in a setting without sound surveillance and reporting system. China should reconsider its definition of imported malaria which neglects imported malaria by mosquitoes and asymptomatic parasite carriers.

Keywords: Chinese-Myanmar border; Linear regression analysis; Malaria.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Carrier State / epidemiology
  • China / epidemiology
  • Cross-Sectional Studies
  • Culicidae / parasitology
  • Disease Transmission, Infectious*
  • Humans
  • Linear Models
  • Malaria / epidemiology*
  • Malaria / transmission
  • Myanmar / epidemiology
  • Prevalence
  • Transients and Migrants