Key Factors Influencing the Incidence of West Nile Virus in Burleigh County, North Dakota

Hiroko Mori, Joshua Wu, Motomu Ibaraki and Franklin W. Schwartz
Additional contact information
Hiroko Mori: Environmental Science Graduate Program, The Ohio State University, Columbus, OH 43210, USA
Joshua Wu: College of Public Health, The Ohio State University, Columbus, OH 43210, USA
Motomu Ibaraki: School of Earth Sciences, The Ohio State University, Columbus, OH 43210, USA
Franklin W. Schwartz: School of Earth Sciences, The Ohio State University, Columbus, OH 43210, USA

IJERPH, 2018, vol. 15, issue 9, 1-19

Abstract: The city of Bismarck, North Dakota has one of the highest numbers of West Nile Virus (WNV) cases per population in the U.S. Although the city conducts extensive mosquito surveillance, the mosquito abundance alone may not fully explain the occurrence of WNV. Here, we developed models to predict mosquito abundance and the number of WNV cases, independently, by statistically analyzing the most important climate and virus transmission factors. An analysis with the mosquito model indicated that the mosquito numbers increase during a warm and humid summer or after a severely cold winter. In addition, river flooding decreased the mosquito numbers. The number of WNV cases was best predicted by including the virus transmission rate, the mosquito numbers, and the mosquito feeding pattern. This virus transmission rate is a function of temperature and increases significantly above 20 °C. The correlation coefficients ( r ) were 0.910 with the mosquito-population model and 0.620 with the disease case model. Our findings confirmed the conclusions of other work on the importance of climatic variables in controlling the mosquito numbers and contributed new insights into disease dynamics, especially in relation to extreme flooding. It also suggested a new prevention strategy of initiating insecticides not only based on mosquito numbers but also 10-day forecasts of unusually hot weather.

Keywords: West Nile Virus; statistical modeling; North Dakota; Culex tarsalis; flooding (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1660-4601/15/9/1928/pdf (application/pdf)
https://www.mdpi.com/1660-4601/15/9/1928/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:15:y:2018:i:9:p:1928-:d:167811

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().