Abstract
BACKGROUND: Zika virus (ZIKV) transmission has been reported in 67 countries/territories in the Oceania region and the Americas since 2015, prompting the World Health Organization (WHO) to declare ZIKV as a Public Health Emergency of International Concern in February 2016, due to its strong association with medical complications such as microcephaly and Guillain-Barré Syndrome (GBS). However, a substantial gap in knowledge still exists regarding differing temporal pattern and potential of transmission of ZIKV in different regions of the world. METHODS: We use a phenomenological model to ascertain the temporal patterns and transmission potential of ZIKV in various countries/territories, by fitting the model to Zika case data from Yap Island and French Polynesia in the Oceania region and 11 countries/territories with confirmed case data, namely, Colombia, Ecuador, French Guiana, Guadeloupe, Guatemala, Mexico, Nicaragua, Panama, Puerto Rico, Saint Martin, and Suriname, to pinpoint the waves of infections in each country/territory and to estimate the respective basic reproduction number R(0). RESULTS: Six of these time series datasets resulted in statistically significant model fit of at least one wave of reported cases, namely that of French Polynesia, Colombia, Puerto Rico, Guatemala, Suriname and Saint Martin. However, only Colombia and Guatemala exhibited two waves of cases while the others had only one wave. Temporal patterns of the second wave in Colombia and the single wave in Suriname are very similar, with the respective turning points separated by merely a week. Moreover, the mean estimates of R(0) for Colombia, Guatemala and Suriname, all land-based populations, range between 1.05 and 1.75, while the corresponding mean estimates for R(0) of island populations in French Polynesia, Puerto Rico and Saint Martin are significantly lower with a range of 5.70-6.89. We also fit the Richards model to Zika case data from six main archipelagos in French Polynesia, suggesting the outbreak in all six island populations occurred during the same time, albeit with different peak time, with mean R(0) range of 3.09-5.05. DISCUSSION: Using the same modeling methodology, in this study we found a significant difference between transmissibility (as quantified by R(0)) in island populations as opposed to land-based countries/territories, possibly suggesting an important role of geographic heterogeneity in the spread of vector-borne diseases and its future course, which requires further monitoring. Our result has potential implications for planning respective intervention and control policies targeted for island and land-based populations.