Liu J, Platts-Mills JA, Juma J, Kabir F, Nkeze J, Okoi C, et al. Use of quantitative molecular diagnostic methods to identify causes of diarrhoea in children: a reanalysis of the GEMS case-control study. Lancet. 2016;388(10051):1291–301.
Article CAS PubMed PubMed Central Google Scholar
O’Donoghue PJ. Cryptosporidium and cryptosporidiosis in man and animals. Int J Parasitol. 1995;25(2):139–95.
Article CAS PubMed Google Scholar
Gururajan A, Rajkumari N, Devi U, Borah P. Cryptosporidium and waterborne outbreaks—a mini review. Trop Parasitol. 2021;11(1):11–5.
Article PubMed PubMed Central Google Scholar
Dong S, Yang Y, Wang Y, Yang D, Yang Y, Shi Y, et al. Prevalence of Cryptosporidium Infection in the global population: a systematic review and meta-analysis. Acta Parasitol. 2020;65(4):882–9.
Han F, Wang L, Wang RZ, Ge JJ, Shen JP. Investigation of cryptopsoridiosis in humans in Nanjing, China. Chin J Zoonoses. 1989;5(5):51.
Liu A, Gong B, Liu X, Shen Y, Wu Y, Zhang W, et al. A retrospective epidemiological analysis of human Cryptosporidium infection in China during the past three decades (1987–2018). PLoS Negl Trop Dis. 2020;14(3): e0008146.
Article PubMed PubMed Central Google Scholar
Yin J, Shen Y, Cao J. Burden of Cryptosporidium infections in the Yangtze River Delta in China in the 21st century: a one health perspective. Zoonoses. 2022;2(1):7.
Wang X, Shen YJ, Cao JP. Epidemic status and prevention and control process of cryptosporidiosis in China. J Trop Dis Parasitol. 2022;20(3):136–48.
Sillero N, Arenas-Castro S, Enriquez-Urzelai U, Vale CG, Sousa-Guedes D, Martínez-Freiría F, et al. Want to model a species niche? A step-by-step guideline on correlative ecological niche modelling. Ecol Model. 2021;456: 109671.
Barbosa MA, Sillero N, Martínez-Freiría F, Real R. Ecological niche models in mediterranean herpetology: past, present and future. In: Zhang WJ, editor. Ecological Niche Models in Mediterranean Herpetology. New York: Nova Science Publishers; 2012. p. 173–204.
Busby JR. BIOCLIM: a bioclimate analysis and prediction system. In: Margules CR, Austin MP, editors. Nature conservation: cost effective biological surveys and data analysis. Melbourne: CSIRO; 1991. p. 64–8.
Stockwell DRB. The GARP modelling system: Problems and solutions to automated spatial prediction. Int J Geogr Inf Sci. 1999;13(2):143–58.
Carpenter G, Gillison AN, Winter J. DOMAIN: a flexible modelling procedure for mapping potential distributions of plants and animals. Biodivers Conserv. 1993;2(6):667–80.
Phillips SJ, Anderson RP, Schapire RE. Maximum entropy modeling of species geographic distributions. Ecol Model. 2006;190:231–59.
Escobar LE, Qiao H, Lee C, Phelps NBD. Novel methods in disease biogeography: a case study with heterosporosis. Front Vet Sci. 2017;4:105.
Article PubMed PubMed Central Google Scholar
Escobar LE, Craft ME. Advances and limitations of disease biogeography using ecological niche modeling. Front Microbiol. 2016;7:1174.
Article PubMed PubMed Central Google Scholar
Escobar LE, Carver S, Romero-Alvarez D, VandeWoude S, Crooks KR, Lappin MR, Craft ME. Inferring the ecological niche of Toxoplasma gondii and Bartonella spp. in wild felids. Front Vet Sci. 2017;4:172.
Article PubMed PubMed Central Google Scholar
Mirzanejad-Asl H, Karimi A, Babaei Pouya N, Moradi-Asl E. Spatio-temporal analysis and determination of the ecological niche model of Giardia Lamblia (Lambl, 1859) in Ardabil province, northwestern Iran. J Parasit Dis. 2021;45(3):706–14.
Article PubMed PubMed Central Google Scholar
Garrido R, Bacigalupo A, Peña-Gómez F, Bustamante RO, Cattan PE, Gorla DE, et al. Potential impact of climate change on the geographical distribution of two wild vectors of Chagas disease in Chile: Mepraia spinolai and Mepraia gajardoi. Parasit Vectors. 2019;12(1):478.
Article PubMed PubMed Central Google Scholar
Meshgi B, Majidi-Rad M, Hanafi-Bojd AA, Fathi S. Ecological niche modeling for predicting the habitat suitability of fascioliasis based on maximum entropy model in southern Caspian Sea littoral, Iran. Acta Trop. 2019;198: 105079.
Kuhn T, Cunze S, Kochmann J, Klimpel S. Environmental variables and definitive host distribution: a habitat suitability modelling for endohelminth parasites in the marine realm. Sci Rep. 2016;6:30246.
Article CAS PubMed PubMed Central Google Scholar
Slater H, Michael E. Predicting the current and future potential distributions of lymphatic filariasis in Africa using maximum entropy ecological niche modelling. PLoS ONE. 2012;7(2): e32202.
Article CAS PubMed PubMed Central Google Scholar
Escobar LE. Ecological niche modeling: an introduction for veterinarians and epidemiologists. Front Vet Sci. 2020;7: 519059.
Article PubMed PubMed Central Google Scholar
Hu WB, Mengersen K, Fu SY, Tong SL. The use of ZIP and CART to model cryptosporidiosis in relation to climatic variables. Int J Biometeorol. 2010;54(4):433–40.
Gonzalez-Moreno O, Hernandez-Aguilar RA, Piel AK, Stewart FA, Gracenea M, Moore J. Prevalence and climatic associated factors of Cryptosporidium sp. infections in savanna chimpanzees from Ugalla, Western Tanzania. Parasitol Res. 2013;112(1):393–9.
Young I, Smith BA, Fazil A. systematic review and meta-analysis of the effects of extreme weather events and other weather-related variables on Cryptosporidium and Giardia in fresh surface waters. J Water Health. 2015;13(1):1–17.
Ikiroma IA, Pollock KG. Influence of weather and climate on cryptosporidiosis-a review. Zoonoses Public Health. 2021;68(4):285–98.
Wang X, Wang X, Cao J. Environmental factors associated with Cryptosporidium and Giardia. Pathogens. 2023;12(3):420.
Article CAS PubMed PubMed Central Google Scholar
Jagai JS, Castronovo DA, Monchak J, Naumova EN. Seasonality of cryptosporidiosis: a meta-analysis approach. Environ Res. 2009;109(4):465–78.
Article CAS PubMed PubMed Central Google Scholar
Polley L, Thompson RC. Parasite zoonoses and climate change: molecular tools for tracking shifting boundaries. Trends Parasitol. 2009;25(6):285–91.
Article CAS PubMed Google Scholar
Rohr JR, Dobson AP, Johnson PT, Kilpatrick AM, Paull SH, Raffel TR, et al. Frontiers in climate change-disease research. Trends Ecol Evol. 2011;26(6):270–7.
Article PubMed PubMed Central Google Scholar
Carlson CJ, Burgio KR, Dougherty ER, Phillips AJ, Bueno VM, Clements CF, et al. Parasite biodiversity faces extinction and redistribution in a changing climate. Sci Adv. 2017;3(9): e1602422.
Article PubMed PubMed Central Google Scholar
Pickles RS, Thornton D, Feldman R, Marques A, Murray DL. Predicting shifts in parasite distribution with climate change: a multitrophic level approach. Glob Chang Biol. 2013;19(9):2645–54.
Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A. Very high resolution interpolated climate surfaces for global land areas. Int J Climatol. 2005;25(15):1965–78.
Fick SE, Hijmans RJ. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. Int J Climatol. 2017;37(12):4302–15.
Karger DN, Conrad O, Böhner J, Kawohl T, Kreft H, Soria-Auza RW, et al. Climatologies at high resolution for the earth’s land surface areas. Sci Data. 2017;4: 170122.
Article PubMed PubMed Central Google Scholar
Moss RH, Edmonds JA, Hibbard KA, Manning MR, Rose SK, van Vuuren DP, et al. The next generation of scenarios for climate change research and assessment. Nature. 2010;463:747–56.
Article CAS PubMed Google Scholar
Yukimoto S, Kawai H, Koshiro T, Oshima N, Yoshida K, Urakawa SL, et al. The Meteorological Research Institute Earth System Model Version 2.0, MRI-ESM2.0: description and basic evaluation of the physical component. J Meteorol Soc JPN. 2019;97(5):931–65.
Jiang Y, Yuan Z, Liu H, Yin J, Qin Y, Jiang X, et al. Intestinal protozoan infections in patients with Diarrhea—Shanghai Municipality, Zhenjiang City, and Danyang City, China, 2011–2015 and 2019–2021. China CDC Wkly. 2022;4(8):143–7.
Article PubMed PubMed Central Google Scholar
ESRI. ArcGIS Desktop: Release 10. Redlands, CA: Environmental Systems Research Institute. 2011.
IMB Corp. IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp. 2019.
Li J, Miao B, Wang S, Dong W, Xu H, Si C, et al. Hiplot: a comprehensive and easy-to-use web service for boosting the publication-ready biomedical data visualization. Brief Bioinform. 2022;23(4):bbac261.
留言 (0)