Written by Ajit Karna is a 2016-2017 Sustainability Leadership Fellow and Ph.D. Candidate in the Department of Microbiology, Immunology, and Pathology.
I have always been fascinated with viruses, ways to detect them earlier, and stop their spread before they make people sick. In the Animal Disease Laboratory at Colorado State University, we do experiments to explore the role animals play in emerging virus transmission including Zika virus. We do not fully understand the sources of the Zika virus yet. In this blog, I explore options available to bridge scientists and policy makers in the development of sustainable solutions to contain the spread of this virus.
Zika virus is a mosquito borne virus, first discovered in a rhesus monkey in the Ziika forest of Uganda in 1947. Until recently, Zika virus outbreaks have been spotty, but a massive outbreak in Brazil in 2015 and its association with incomplete development of fetal brain (microcephaly) in pregnant women with the Zika virus infection made the current Zika virus outbreak a public health emergency. We do not have fully understood the factors that resulted in this sudden geographic spread and emergence of birth defects. There is no vaccine or medicine available for the prevention and treatment of Zika virus. Transmission (see figure) primarily occurs by the bites of Aedes mosquitoes carrying the virus but the transmission of the virus through sexual contact between person to person increases the likelihood of transmission. The inadequacy of data from previous outbreaks has impeded the science community’s ability to predict the course of Zika virus and inform the policy makers to take evidence-based actions.
The importance of forecasting the next outbreak in human populations and how best to allocate, use and mobilize the monetary, physical and human resources is well demonstrated by the Ebola virus outbreak in West Africa. The predictions can help policy-makers understand the magnitude, duration, and consequences of such outbreaks in human populations, and to manage the outbreaks effectively and sustainably. Even in the absence of detailed data on Zika virus, we can learn a lot from other closely related mosquito borne viruses including dengue virus and yellow fever virus. Database on dengue and yellow fever viruses can be used to derive and synthesize empirical data on outbreak and transmission of Zika virus. The resulting approximated data along with known outbreak patterns of Zika virus can be modeled under different modelling approaches. Using mathematical models, we can figure out some of the unanswered questions, such as the relative role of sexual contact adds to the mosquito bites, and sylvatic, or animal, cycle to the urban cycle in current Zika virus transmission context (see figure). Scientists using the data only on mosquito transmittable viruses need to be mindful that Zika virus is also sexually transmittable. In addition, data on dengue or yellow fever diseases do not reflect observed patterns in Zika. For instance, women have 80% or higher incidence of Zika infection than men in Brazil, perhaps associated with an exponential increase in women visits to a doctor during the epidemic.
The unique property of Zika virus adds complexity in designing a mathematical model to answer several questions. In such situations, mathematical modelers can take into consideration these differences and work through different types of models for (i) only sexually transmitted scenario, (ii) combined sexually and mosquito transmitted scenarios, and (iii) only mosquito transmitted scenario. For (i) and (iii), it will be useful to use data from other purely sexually transmitted disease systems or purely mosquito transmitted disease systems. The combined sexual and mosquito transmitted scenario can be a little tricky to model and even more difficult to parameterize appropriately. Dynamic and compartmental models can be used to formulate hypotheses, and increasing availability of data will allow testing these hypotheses. Among many, one approach to estimate the proportion of sexually transmitted cases compared with the proportion of mosquito transmitted cases of Zika virus is through an integrated biological-behavioral surveillance approach in communities where clinical settings are ongoing. This approach can also be used to untangle human exposure to virus via animal reservoir (sylvatic) compared with urban sources (e.g. Human-mosquito-human transmission). Once we know the incubation period of Zika virus in humans and mosquitoes, frequency of mosquito bites, relative density of the mosquitoes, and proportion of the blood-fed mosquitoes, we can use them to forecast the current Zika virus epidemic in humans. Similarly, the genetic data of the Zika virus isolated from the current and past outbreaks could reveal if the virus from recent outbreaks has new mutations, and may explain the emergence of birth defects that were not observed in previous outbreaks. Before we fully understand the transmission and course of the spread, these models will add possible randomly determined data or pattern that the existing data may not inform, and help scientists inform policy-makers how to respond early.
While prediction of an outbreak is useful, investing in long-term surveillance programs with training, laboratory capacity building, information systems strengthening and community participation could sustainably contain the spread of the Zika virus. Programs based on community participation can build trust and will likely bring more men and women to the health centers to get tested for Zika virus, thereby preventing sexual transmission from infected cases to non-infected person at least to certain extent. At the same time, virus surveillance in mosquitoes and the mosquito control should be ongoing to detect areas of risk for human transmission. In an outbreak situation, subsidizing the cost of hospital visits, contraceptives, or window and door screens could greatly reduce Zika transmission. In addition, constant national and international support is necessary for such programs to be sustainable. The low and middle income countries can face an extra challenge to stop emergence and spread of Zika virus due to their insufficient monetary and trained human resources. Sustainable scenarios also need to be explored while forecasting the next Zika virus emergence and spread.
Zika virus is an urgent example of how scientists take active roles to protect communities facing uncertain challenges. Existing data, theoretical frameworks, epidemiological and ecological methods can help the scientists forecast the spread and future emergence of Zika virus. Just as data from other mosquito-borne viruses can inform predictions of Zika virus outbreaks, Zika virus may contribute vital information to address emergence of future viruses before they result in an epidemic.