Spatial epidemiological approaches to monitor and measure the risk of human leptospirosis

Abstract

Leptospirosis, a life-threatening yet neglected disease caused by Gram negative spirochete Leptospira, is a zoonotic disease of global public health importance. In China, at least 2.5 million cases have been reported since the 1950s. Although there has been a decline in incidence since the 2000s, leptospirosis remains a major public health issue. The incidence of leptospirosis has remained at a low level in the past few years; this provides opportunities to eliminate the transmission. However, effective control and elimination strategies in China are hindered by considerable knowledge gaps regarding the epidemiology, burden, and the geographical distribution of leptospirosis in the country. There is a need to develop spatial explicit tools to help analyse the spatiotemporal heterogeneity of leptospirosis incidence to provide a necessary evidence base to better inform planning and implementation of targeted leptospirosis surveillance and control strategies.The overall objectives of the program of research are to (1) review and critically evaluate the spatial analytical tools used in leptospirosis studies (Chapter 4); (2) quantify and map the spatial trends of the burden of leptospirosis in China (Chapter 5); (3) explore the geographical pattern and hotspots of leptospirosis incidence, and its socioecological characteristics (Chapter 6); (4) quantify the role of environmental and socioeconomic factors on the spatial variation of leptospirosis incidence and to produce spatially-explicit predictive maps of incidence of leptospirosis (Chapter 7); and 5) assess the association of weather, environmental indicators and leptospirosis incidence to develop localised temporal prediction models (Chapter 8).A total of 115 peer-reviewed published articles were reviewed and critically evaluated; gaps in knowledge and future directions of the use of spatial techniques in the field of human and animal leptospirosis were discussed (Chapter 4). In Chapter 5, I analysed 8158 notified human leptospirosis cases reported during 2005–2016 to estimate geographical variation in the leptospirosis burden. I found that approximately 10,313 disability-adjusted life-years (DALY) were lost due to Leptospira infection during 2005–2015. Those most affected by leptospirosis were males, young populations, and farmers. Of the total DALYs, 30% was from premature death among those aged under 20 years. The spatial analyses in Chapter 6 revealed that the high-risk counties for leptospirosis were clustered and were mainly in the southwest and southern region of China along the Yangtze River and Pearl River. High-risk counties were significantly different in terms of their demographical, environmental, and socioeconomic profiles compared with low-risk counties. The study in Chapter 7 further revealed that the environmental and socioeconomic effects significantly differed between the Upper Yangtze River Basin and the Pearl River Basin, confirming that leptospirosis transmission is highly geographic specific. After accounts for environmental and socioeconomic factors, the Bayesian spatial conditional autoregressive models indicated that the highest leptospirosis incidence was identified throughout the western and southern part of the Upper Yangtze River Basin and in the midstream and lower reaches of the Pearl River Basin (Chapter 7). For timely intervention, the evidence from the study of high-risk counties—Yilong County and Mengla County (Chapter 8)—demonstrated that variability of rainfall and satellite-based physical environmental parameters, including vegetation (indicated by normalized difference vegetation) and flooding (indicated by modified normalized difference water index), can be used as predictors of leptospirosis outbreaks. However, the response and lag effects of such indicators are significantly varied between locations.This thesis demonstrates that spatial epidemiological tools have benefited the understanding of the epidemiology of leptospirosis in China and they can be further used to support intervention programs to eliminate transmission of leptospirosis in the residual hotspots. This thesis lays a foundation for further development of an integrated spatial-temporal decision support system for leptospirosis control to support health authorities in planning and implementing effective and timely spatially targeted public health interventions in the identified residual high-risk regions.