RESUMO
The international spread of Zika virus (ZIKV) began in Brazil in 2015. To estimate the riskof observing imported ZIKV cases, we calculated effective distance, typically an excellent predictorof arrival time, from airline network data. However, we eventually concluded that, for ZIKV, effectivedistance alone is not an adequate predictor of arrival time, which we partly attributed to the difficultyof diagnosing and ascertaining ZIKV infections. Herein, we explored the mechanisms behind theobserved time delay of ZIKV importation by country, statistically decomposing the delay into twoparts: the actual time to importation from Brazil and the reporting delay. The latter was modeled as afunction of the gross domestic product (GDP) and other variables that influence underlying diagnosticcapacity in a given country. We showed that a high GDP per capita is a good predictor of shortreporting delay. ZIKV infection is generally mild and, without substantial laboratory capacity, casescan be underestimated. This study successfully demonstrates this phenomenon and emphasizes theimportance of accounting for reporting delays as part of the data generating process for estimatingtime to importation.
Assuntos
Doenças Transmissíveis Importadas/virologia , Infecção por Zika virus/epidemiologia , Infecção por Zika virus/transmissão , Brasil/epidemiologia , Controle de Doenças Transmissíveis , Doenças Transmissíveis Importadas/epidemiologia , Doenças Transmissíveis Importadas/transmissão , Epidemias , Humanos , Funções Verossimilhança , Modelos Teóricos , Análise de Regressão , Fatores de Risco , América do Sul/epidemiologia , Viagem , Zika virusRESUMO
Emerging and re-emerging dengue fever has posed serious problems to public health officials in many tropical and subtropical countries. Continuous traveling in seasonally varying areas makes it more difficult to control the spread of dengue fever. In this work, we consider a two-patch dengue model that can capture the movement of host individuals between and within patches using a residence-time matrix. A previous two-patch dengue model without seasonality is extended by adding host demographics and seasonal forcing in the transmission rates. We investigate the effects of human movement and seasonality on the two-patch dengue transmission dynamics. Motivated by the recent Peruvian dengue data in jungle/rural areas and coast/urban areas, our model mimics the seasonal patterns of dengue outbreaks in two patches. The roles of seasonality and residence-time configurations are highlighted in terms of the seasonal reproduction number and cumulative incidence. Moreover, optimal control theory is employed to identify and evaluate patch-specific control measures aimed at reducing dengue prevalence in the presence of seasonality. Our findings demonstrate that optimal patch-specific control strategies are sensitive to seasonality and residence-time scenarios. Targeting only the jungle (or endemic) is as effective as controlling both patches under weak coupling or symmetric mobility. However, focusing on intervention for the city (or high density areas) turns out to be optimal when two patches are strongly coupled with asymmetric mobility.