Zika and Chickungunya have posed
serious health problems for populations in the Americas for the past several
years, but recently, a new study has provided a way to predict epidemics in
this region, specifically in Rio de Janeiro that would be beneficial in
preparing and minimizing damage from outbreaks. Fuller and his peers have
recently published a paper looking at statistical and simulation models that
looked at variables such as social-economic risk factors for having Zika and
Chickungunya (having running water or stored water), incubation periods of the
viruses, and rainfall as a predictor for epidemics.
The results of these models showed
that individuals with a lower SES had a greater risk of contracting Zika and
Chikungunya, and that rainfall is usually followed by an outbreak of Zika and
Chikungunya two to three weeks later. In the case of the largest Zika outbreak
to date that occurred late October 2015, it is interesting to note that
Chickungunya did not spread across the region concurrently with Zika. Why? Well,
the models also elucidates the idea that two viruses can compete with each
other for adequate transmission and survival through a vector, which in this
case is the mosquito species Aedes aegypti. It turns out that the infectious
period of a virus is a key factor in determining whether the virus will go extinct
or not in a region. In the case of Chickungunya which had a high infectious
period contrasted to the relatively lower Zika infectious period, it is
predicted that Chickungunya was outcompeted, but was later reintroduced in 2015
after the major Zika outbreak, which coincides with the start of the
Chickungunya outbreak shortly after the Zika outbreak. Incubation periods were
also shown to determine in what order the outbreaks happened. As Zika had an
incubation period of approximately 10 days, and Chikungunya had an incubation
period of around 2-4 days, it is clear that Chickungunya spreads significantly faster
through arboviral transmission, which is why we also see Chickungunya
outcompeting Zika over time and thus explains why Chikungunya epidemics usually
happen after Zika epidemics.
To minimize damage caused by these
epidemics, it was suggested that an early warning system based on weather models
be utilized to prepare and warn policy makers and clinicians to better deal with
the outbreaks. For example, physicians would have ample time to make sure that enough
immunoglobulin supply is at hand to treat patients with Guillan-Barre Syndrome
caused by Zika.
Looking forward, I am optimistic that
even more models that predict viral outbreaks and epidemics will be made and
that millions of individuals will benefit as a result.
-Daniel
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