A recent study published in PLos One analyzed the incidence data of typhoid and paratyphoid fevers between 2004 and 2016 in China, to explore the epidemiological features such as age-specific and geographical distribution.

This was a descriptive study employed Grey model GM (1,1) and seasonal autoregressive integrated moving average (SARIMA) model to extract long-term trends of the diseases.

The findings revealed that cumulative incidences of both fevers encountered significant decrease nationally—showing a drop of 73.9% for typhoid and 86.6% for paratyphoid—in 2016 from 2004. While the cumulative incidence fell in all age subgroups, 0-4 years-old children were the most susceptible ones in recent years. On the other hand, a cluster of three southwestern provinces – Yunnan, Guizhou and Guangxi, were top high-incidence regions. Predictive models for both fevers forecasted that cumulative incidence would continue the slightly downward trend and maintain cyclical seasonality in the upcoming years. 

It was inferred that such data-driven insights are informative and actionable for the prevention and control of serious infectious diseases like typhoid and paratyphoid fevers.

Source: PLoS One. 2020 Oct 28;15(10):e0241217. doi: 10.1371/journal.pone.0241217.