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| M | R | C | C | West Nile Virus
Mosquito Crossover Dates
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Two mosquito species – Culex restuans,
the white-spotted mosquito, and Culex pipiens, the northern
house mosquito – are believed to maintain the natural transmission
cycle of West Nile Virus (WNV) between birds and mosquitoes. The population
of northern house mosquitoes, the primary suspect for WNV transmission
to humans, is low in spring but grows to become the dominant species
later in summer, especially in urban areas. Research has found that a
rise of West Nile infection in mosquitoes parallels the rise in abundance
of the northern house mosquito The term “crossover” is defined
here as the time when the relative proportions are equal during this
transition from an early season dominance of Culex restuans and
a late season dominance of Culex pipiens. . The peak infection
rate in mosquitoes occurs about two to three weeks after the northern
house mosquito becomes the dominant species. This peak in infection obviously
represents the period of greatest risk of transmission to incidental
hosts such as horses, humans and other wildlife. On average, crossover occurs in early August. However, there is considerable variability from year to year, ranging from early July to mid September. This variation introduces considerable variation from year to year in the risk of WNV infection. Recent research indicates that simple models based on temperature are able to explain much of the variance in the crossover date. Two models are used here. One is based on the number of days when the maximum temperature exceeds 81°F. The second is based on degree days with a base of 63°F. Additional research has shown that inclusion of Model Output Statistics (MOS) allows for a more timely (on average a 7-day lead time) forecast of the crossover date. MOS is a technique used to objectively interpret model output and produce site specific (Champaign-Urbana) guidance. These two models are used here to provide a probabilistic assessment of the likely crossover time. The approach used here is very simple:
Specifically, each year in the historical climate
database is assumed to be one scenario for the outcome of the remainder
of the year. To apply this concept, the temperature time series for one
scenario is assumed to be the combination of the actual observed data
up to today’s date, plus MOS forecasted temperatures for the next ten days, plus the observed temperature data from some
past year for all days beginning 11 days out from the current day. We then use the two models
to estimate the crossover date. This process is repeated over 100 times using
each year from 1900 to last year as a possible scenario for the remainder of
this year. These predicted crossover dates are sorted from earliest to latest day of
year. The result is a probability distribution of crossover dates; thus,
this provides an estimate of both the variance and the mean of estimated
crossover date.
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