The non-stationary and spatially varying associations between hand,foot and mouth disease and multiple environmental factors:A Bayesian spatiotemporal mapping model study

The transmission and prevalence of Hand,Foot and Mouth Disease(HFMD)are affected by a variety of natural and socio-economic environmental factors.This study aims to quantitatively investigate the non-stationary and spatially varying associations between various environmental factors and HFMD risk.We collected HFMD surveillance cases and a series of relevant environmental data from 2013 to 2021 in Xi'an,Northwest China.By controlling the spatial and temporal mixture effects of HFMD,we constructed a Bayesian spatiotemporal mapping model and characterized the impacts of different driving factors into global linear,non-stationary and spatially varying effects.The results showed that the impact of meteorological conditions on HFMD risk varies in both type and magnitude above certain thresholds(temperature:30°C,precipitation:70 mm,solar radiation:13000 kJ/m^(2),pressure:945 hPa,humidity:69%).Air pollutants(PM_(2.5),PM_(10),NO_(2))showed an inverted U-shaped relationship with the risk of HFMD,while other air pollutants(O_(3),SO_(2))showed nonlinear fluctuations.Moreover,the driving effect of increasing temperature on HFMD was significant in the 3-year period,while the inhibitory effect of increasing precipitation appeared evident in the 5-year period.In addition,the proportion of urban/suburban/rural area had a strong influence on HFMD,indicating that the incidence of HFMD firstly increased and then decreased during the rapid urbanization process.The influence of population density on HFMD was not only limited by spatial location,but also varied between high and low intervals.Higher road density inhibited the risk of HFMD,but higher night light index promoted the occurrence of HFMD.Our findings further demonstrated that both ecological and socioeconomic environmental factors can pose multiple driving effects on increasing the spatiotemporal risk of HFMD,which is of great significance for effectively responding to the changes in HFMD epidemic outbreaks.

Diagnosing and reintegrating traceability of infectious diseases via metagenomic next-generation sequencing:Study of a severe case of Rickettsia japonica infection

Background:In this study,we present a case of Japanese spotted fever(JSF)caused by Rickettsia japonica and use this case to investigate the process of diagnosing and reintegrating traceability of infectious diseases via metagenomic next-generation sequencing(mNGS).Methods:From data relating to epidemiological history,clinical and laboratory examinations,and mNGS se-quencing,a diagnosis of severe JSF was concluded.Results:A detailed field epidemiological investigation discovered parasitic Haemaphysalis longicornis from a host animal(dog)in the domicile of the patient,within which R.japonica was detected,along with a diverse array of other potentially pathogenic microorganisms that could cause other infectious diseases.Conclusion:The mNGS provided an efficient method to diagnose JSF infection.This methodology could also be applied to field epidemiological investigations to establish the traceability of infectious diseases.

Monkeypox virus 2022,gene heterogeneity and protein polymorphism

Dear Editor,Human monkeypox(MPX),an endemic disease in equatorial Africa,1 has been causing outbreaks in non-endemic countries since early May 2022.Interestingly,many confirmed cases have no history of travel to Africa.This is the first time many MPX cases have been reported concurrently in both non-endemic and endemic countries in disparate geographical areas.2 In response,we have analyzed 27 genes or sequences from 643 full-length human monkeypox virus(MPXV)genomes collected after January 1 and submitted by August 7,2022(Supplementary Table 1).We divided these 643 genomes into 24 clusters with a 95%identity threshold(Supplementary Table 2).