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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