Spatio-temporal trends and risk factors for Shigella from 2001 to 2011 in Jiangsu Province, People's Republic of China

PLoS One. 2014 Jan 8;9(1):e83487. doi: 10.1371/journal.pone.0083487. eCollection 2014.

Abstract

Objective: This study aimed to describe the spatial and temporal trends of Shigella incidence rates in Jiangsu Province, People's Republic of China. It also intended to explore complex risk modes facilitating Shigella transmission.

Methods: County-level incidence rates were obtained for analysis using geographic information system (GIS) tools. Trend surface and incidence maps were established to describe geographic distributions. Spatio-temporal cluster analysis and autocorrelation analysis were used for detecting clusters. Based on the number of monthly Shigella cases, an autoregressive integrated moving average (ARIMA) model successfully established a time series model. A spatial correlation analysis and a case-control study were conducted to identify risk factors contributing to Shigella transmissions.

Results: The far southwestern and northwestern areas of Jiangsu were the most infected. A cluster was detected in southwestern Jiangsu (LLR = 11674.74, P<0.001). The time series model was established as ARIMA (1, 12, 0), which predicted well for cases from August to December, 2011. Highways and water sources potentially caused spatial variation in Shigella development in Jiangsu. The case-control study confirmed not washing hands before dinner (OR = 3.64) and not having access to a safe water source (OR = 2.04) as the main causes of Shigella in Jiangsu Province.

Conclusion: Improvement of sanitation and hygiene should be strengthened in economically developed counties, while access to a safe water supply in impoverished areas should be increased at the same time.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China / epidemiology
  • Dysentery, Bacillary / epidemiology*
  • Geography
  • Humans
  • Incidence
  • Risk Factors
  • Seasons
  • Spatio-Temporal Analysis*
  • Time Factors

Grants and funding

This work was supported in part by Natural Science Foundation Key Project of Jiangsu Province, China (BK2010079), “National S&T Major Project Foundation of China” (2011ZX10004-902), Jiangsu Province Health Development Project with Science and Education (NO.ZX201109), and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.