Figure - PMC

Skip to main content

An official website of the United States government

Here's how you know

Here's how you know

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

View full-text article in PMC

. 2009 Sep 1;6(9):e1000139. doi: 10.1371/journal.pmed.1000139

Search in PMC
Search in PubMed
View in NLM Catalog
Add to search

This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.

This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.

PMC Copyright notice

(A) Estimates of the force of infection (per year) for each year, 1980–2005 in Thailand estimated using age-specific case data aggregated at the national level and model 3 (see Text S1). 95% CIs are indicated by vertical bars. The line drawn is the least squares linear regression weighted using the reciprocal of width of CIs on each point. This linear trend shows a reduction in the force of infection of 0.002 per year (p<1e−6). (B) Histogram of mean forces of infection averaged over the interval 1985–2005 estimated using data from each of the 72 provinces of Thailand. Histogram shows the frequency of 72 estimates occurring in the ranges indicated on the x-axis. (C) Histogram of changes in forces of infection over the interval 1985–2005 estimated using data from each of the 72 provinces of Thailand. Histogram shows the frequency of 72 estimates of the change in force of infection occurring in the ranges indicated on the x-axis. We estimated changes using weighted least squares regression of annual estimates of the force of infection in each location.