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Interrelationship of soil moisture and temperature to sylvatic plague cycle among prairie dogs in the Western United States

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Integrative Zoology 2021年第6期16卷 852-867页

作者： Cassandra D.PAULING Deborah L.FINKE Deborah M.ANDERSON Department of Veterinary Pathobiology University of MissouriColumbiaMissouriUSA Division of Plant Sciences University of MissouriColumbiaMissouriUSA

Plague,caused by Yersinia pestis,is a flea-borne disease that is endemic in areas throughout the world due to its successful maintenance in a sylvatic cycle,mainly in areas with temperate climates.Burrowing rodents are thought to play a key role in the enzootic maintenance as well as epizootic outbreaks of plague.In the United States,prairie dogs(Cynomys),rodents(Muridae),and ground squirrels(Spermophilus)are susceptible to infection and are parasitized by fleas that transmit plague.In particular,prairie dogs can experience outbreaks that rapidly spread,which can lead to extirpation of colonies.A number of ecological parameters,including climate,are associated with these epizootics.In this study,we asked whether soil parameters,primarily moisture and temperature,are associated with outbreaks of plague in black-tailed prairie dogs and Gunnison’s prairie dogs in the Western United States,and at what depth these associations were apparent.We collected publicly available county-level information on the occurrence of population declines or colony extirpation,while historical soil data was collected from SCAN and USCRN stations in counties and states where prairie dogs have been located.The analysis suggests that soil moisture at lower depths correlates with colony die-offs,in addition to temperature near the surface,with key differences within the landscape ecology that impact the occurrence of plague.Overall,the model suggests that the burrow environment may play a significant role in the epizootic spread of disease amongst black-tailed and Gunnison’s prairie dogs.

关键词： plague prairie dogs soil moisture soil temperature sylvatic cycle Yersinia pestis

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Assessing the risk of spread of Zika virus under current and future climate scenarios

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Biosafety and Health 2022年第3期4卷 193-204页

作者： Ye Xu Jingni Zhou Tong Liu Peiwen Liu Yang Wu Zetian Lai Jinbao Gu Xiaoguang Chen Department of Pathogen Biology Key Laboratory of Tropical Disease Research of Guangdong ProvinceSchool of Public HealthSouthern Medical UniversityGuangzhou 510515China Institute of Tropical Medicine School of Public HealthSouthern Medical UniversityGuangzhou 510515China

Zika virus(ZIKV)may cause severe microcephaly in newborn babies and Guillain‐Barrésyndrome in some adults.In recent decades,its range has expanded in 86 countries.There are two ecologically and evolutionarily district cycles:urban cycle and sylvatic cycle.This work aimed to estimate the urban and sylvatic cycle areas of ZIKV throughout the world.The occurrence records of vectors,non‐human primate hosts,and ZIKV were collected.We chose historical climate data,predicted vectors distribution,human population density,and elevation data as the variables to fit the maximum entropy model(MaxEnt).Current risk area and future prediction were performed with global climate models(GCMs)and shared socioeconomic pathways(SSPs).Predicting the ZIKV risk area would help tailor related control strategies.The results indicated that 16.6%of the world’s landmass(except Antarctica)is a risk area in the urban cycle.Approximately 6.22 billion people(78.69%of the global population)live in the risk area,with the vast majority in South Asia,tropical Africa,South America,North America,and countries around the Mediterranean Sea.Future climate change decreases the risk area of ZIKV.This study also suggested that the sylvatic cycle happened between the Tropic of Cancer and the Tropic of Capricorn.The overlap region of the urban and sylvatic cycles could be hotpots that ZIKV spill from the sylvatic to the urban cycle.It is indicated that long‐term passenger screening,mosquito surveillance,and control are necessary.

关键词： Zika virus Aedes aegypti Aedes albopictus Species distribution modeling MaxEnt Urban cycle sylvatic cycle

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