Analysis of the effect of meteorological factors on hemorrhagic fever with renal syndrome in Taizhou City, China, 2008–2020

Abstract

Background Hemorrhagic fever with renal syndrome (HFRS) is endemic in Zhejiang Province, China, while few studies have concentrated on the influence of meteorological factors on HFRS incidence in the area. Methods Data on HFRS and meteorological factors from January 1, 2008 to December 31, 2020 in Taizhou City, Zhejiang Province were collected. Multivariate analysis was conducted to the relationship between meteorological factors including minimum temperatures, relative humidity, and cumulative rainfall with HFRS. Results The HFRS incidence peaked in November and December and it was negatively correlated with average and highest average temperatures. Compared with median of meteorological factors, the relative risks (RR) of weekly average temperature at 12 ℃, weekly highest temperature at 18 ℃relative humidity at 40%, and cumulative rainfall at 240 mm were most significant and RRs were 1.41 (95% CI: 1.09–1.82), 1.32 (95% CI: 1.05–1.66), 2.18 (95% CI: 1.16–4.07), and 1.91 (95% CI: 1.16–2.73), respectively. Average temperature, precipitation, relative humidity had interactions on HFRS and the risk of HFRS occurrence increased with the decrease of average temperature and the increase of precipitation. Conclusion Our study results are indicative of the association of environmental factors with the HFRS incidence, probable recommendation could be use of environmental factors as early warning signals for initiating the control measure and response.

Assessing the Relationship between Climate Variables and Hemorrhagic Fever with Renal Syndrome Transmission in Eastern China: A Multi-Cities Time Series Study

“…Temperature is the most widely studied meteorological factor for climate-sensitive infectious diseases. It is one of the essential meteorological factors affecting HFRS incidence, with a complicated and nonlinear relationship in previous studies [5,7,8,26]. Our results found that the exposure-response curve for temperature-HFRS incidence was approximately reversed U-shaped, in agreement with an earlier study [27].…”

“…Sun et al [7] found that the risk of HFRS infection was highest when both temperature and precipitation were high. In Taizhou, the risk of HFRS increased with the decreasing average temperature and the increasing precipitation [8]. A geographic distribution analysis indicated that the highest incidence of HFRS was reported in China's semihumid climate with a mountainous geographical structure [35].…”

“…where E(Y t ) denotes the number of weekly reported HFRS cases at week t; α is the intercept; cb means the cross-basis function of the meteorological variable. In this study, M represents mean temperature; week is the ordinal variable of the week in the year to control the long temporal trend; ns represents the nature spline function; Cov is the covariate variable to control the impact of other meteorological factors on week t. This study set the maximum lag period to 16 weeks [7,8].…”

“…HFRS is considered a climatic-sensitive infectious disease, and it is becoming increasingly apparent that variations profoundly impact HFRS dynamics [4][5][6][7][8]. Prior studies had identified distinct climatic impacts that exhibited variations in geographical distribution [9][10][11][12].…”

The Temporal Lagged Relationship Between Meteorological Factors and Scrub Typhus With the Distributed Lag Non-linear Model in Rural Southwest China

“…Since weather factors such as temperature and humidity have been proven to have a significant relationship with the occurrence and transmission of many infectious diseases (9,(32)(33)(34), in our study, the association between weather factors and scrub typhus was explored using DLNM (17,35).…”