Geographical and temporal distribution of the residual clusters of human leptospirosis in China, 2005–2016

Abstract

Human leptospirosis outbreaks still persistently occur in part of China, indicating that leptospirosis remains an important zoonotic disease in the country. Spatiotemporal pattern of the high-risk leptospirosis cluster and the key characteristics of high-risk areas for leptospirosis across the country are still poorly understood. Using spatial analytical approaches, we analyzed 8,158 human leptospirosis cases notified during 2005–2016 across China to explore the geographical distribution of leptospirosis hotspots and to characterize demographical, ecological and socioeconomic conditions of high-risk counties for leptospirosis in China. During the period studied, leptospirosis incidence was geographically clustered with the highest rate observed in the south of the Province of Yunnan. The degree of spatial clustering decreased over time suggesting changes in local risk factors. However, we detected residual high-risk counties for leptospirosis including counties in the southwest, central, and southeast China. High-risk counties differed from low-risk counties in terms of its demographical, ecological and socioeconomic characteristics. In high-risk clusters, leptospirosis was predominantly observed on younger population, more males and farmers. Additionally, high-risk counties are characterized by larger rural and less developed areas, had less livestock density and crops production, and located at higher elevation with higher level of precipitation compare to low-risk counties. In conclusion, leptospirosis distribution in China appears to be highly clustered to a discrete number of counties highlighting opportunities for elimination; hence, public health interventions should be effectively targeted to high-risk counties identified in this study.

Leptospirosis trends in China, 2007–2018: A retrospective observational study

“…The morbidity rate of leptospirosis is influenced by many factors, such as climate (temperature, humidity, rainfall, etc. ), carrier/reservoir populations (density, activity, abundance, amplifier host) and people (immunization coverage, effective antibody levels) (Dhewantara et al, ; Zhang, Wang, et al, ). Previous studies indicated that the morbidity of leptospirosis follows distinct seasonal patterns and is strongly associated with high rainfall amounts and flooding, when leptospires are widely dispersed in the environment.…”

“…In recent years, a couple of studies have been conducted on the prevalence of leptospirosis infection in different animal species and humans in many regions of China (Dhewantara et al, ). The spread of leptospirosis among humans has the significant regional distribution, seasonal characteristic in China, while the leptospirosis infection also tracked closely with gender, age and occupation, while analysis is as follows: Leptospirosis is mainly transmitted by direct contact with infected/carrier animal hosts, exposure to urine from carriers or contact with water sources contaminated with carrier urine.…”

“…Although the incidence of leptospirosis has shown a significant decline in recent years, small‐scale local outbreaks and high prevalence of leptospirosis have been recently reported in some endemic regions of China (Zhang, Li, et al, ; Zhang, Wang, et al, ; Zhang et al, ). Thus, leptospirosis remains an important public health problem domestically (Dhewantara et al, ; Zhang, Wang, et al, ). Moreover, the public (stakeholders: e.g.…”

New Perspectives for Mapping Global Population Distribution Using World Settlement Footprint Products

“…Global or large scale gridded population datasets considered state-of-the-art in terms of open access archives of population distribution data include: the Rural-Urban Mapping Project (GRUMP) [5], the Gridded Population of the World, Version 4 (GPWv4) [6,7], the LandScan Global Population database [8,9], the Global Human Settlement Layer-Population grid (GHS-POP) [10,11], the WorldPop datasets [12][13][14][15][16] and the recently developed High Resolution Settlement Layer (HRSL) population grids [17]. Current and previous versions of these products have proved to be an important source of information and essential input for a wide range of cross-disciplinary applications including: poverty mapping [18][19][20], epidemiological modelling and disease burden estimation [21][22][23], interconnectivity and accessibility analyses [24][25][26], deriving past and future population estimates [15,27,28], disaster management [29][30][31] and human settlement characterisation [32] among others.…”

Spatial super-spreaders and super-susceptibles in human movement networks

“…In other words, by identifying super-susceptible locations, we aim finding the most susceptible nodes within the spatial human movement network. One similar concept in spatial analysis is the low-high outliers, that is any location with low density of disease cases which is surrounded by high density locations, thereby making it more vulnerable as it has a higher probability to report a higher number of cases in the following time period 54 . In the field of network science, the concepts of ‘spreaders’ and ‘receivers’ first appeared in the Hyperlink-Induced Topic Search (HITS) algorithm 22 as hubs and authorities, respectively.…”