The transmission of haemorrhagic fever with renal syndrome (HFRS) is deeply influenced by the reservoir and hantavirus prevalence rate. In this study, a surveillance on human HFRS cases, relative rodent abundance, and hantavirus infection prevalence was conducted in Shaanxi province, China, during 1984–2012. A generalized linear model with Poisson-distributed residuals and a log link was used to quantify the relationship between reservoir, virus and HFRS cases. The result indicated that there was a significant association of HFRS incidence with relative rodent density and the prevalence rate. This research provides evidence that the changes of infection prevalence in the reservoir could lead directly to the emergence of a new epidemic. It was concluded that the measurement of a number of these variables could be used in disease surveillance to give useful advance warning of potential disease epidemics.

The extent of hantavirus seroprevalence in the healthy population from Bosnia and Herzegovina has not yet been investigated; therefore, the aim of this study was to assess the hantavirus seroprevalence in the population from different regions of Bosnia and Herzegovina and in different risk groups. The serosurvey included 1331 subjects from endemic and non-endemic regions in Bosnia and Herzegovina. All sera samples were examined using IgG ELISA, and Western blot (Bunyavirus IgG) tests. Hantavirus seroprevalence was 7·4% in the endemic region and 2·4% in the non-endemic region (P<0·05). Former soldiers from the endemic region had significantly the highest seroprevalence (16·1%) compared to the general population from the endemic region (6·2%), the occupational risk group from the non-endemic region (5·6%) and the general population from the non-endemic region (0·8%) (P<0·01). No difference in hantavirus seroprevalence between gender or age groups was observed. Hantavirus seroprevalence in different populations in Bosnia and Herzegovina was found to be highest compared to other central European countries.

We obtained a list of all reported cases of haemorrhagic fever with renal syndrome (HFRS) in Shenyang, China, during 1990–2003, and used GIS-based scan statistics to determine the distribution of HFRS cases and to identify key areas and periods for future risk-factor research. Spatial cluster analysis suggested three areas were at increased risk for HFRS. Temporal cluster analysis suggested one period was at increased risk for HFRS. Space–time cluster analysis suggested six areas from 1995 to 1996 and four areas from 1998 to 2003 were at increased risk for HFRS. We also discussed the likely reasons for these clusters. We conclude that GIS-based scan statistics may provide an opportunity to classify the epidemic situation of HFRS, and we can pursue future investigations to study the likely factors responsible for the increased disease risk based on the classification.