Modeling Mayaro and Chikungunya Control Strategies in Rio de Janeiro Outbreaks

Abstract

Mosquito-borne diseases have become a significant health issue in many regions around the world. For tropical countries, diseases such as Dengue, Zika, and Chikungunya, became epidemic in the last decades. Health surveillance reports during this period were crucial in providing scientific-based information to guide decision making and resources allocation to control outbreaks. In this work, we perform data analysis of last Chikungunya epidemics in the city of Rio de Janeiro by applying a compartmental mathematical model. We estimate the "basic reproduction number" for those outbreaks and predict the potential epidemic outbreak of Mayaro virus. We also simulated several scenarios with different public interventions to decrease the number of infected people.Such scenarios should provide insights about possible strategies to control future outbreaks. September 5, 2019 2/19 In the last decades, Mosquito-borne diseases have become a significant health issue in 2 many regions around the world. Projections indicate that around 2050, half of the 3 population will be at risk of some arbovirus infection [1]. These arboviruses, which 4 include diseases such as Dengue, Zika, and Chikungunya, are epidemic in most of the 5 tropical countries. Besides temperature and humidity, human migrations and sanitation 6 also contribute to the epidemic conditions in these places [2, 3]. For example, around 7 300.000 people were infected by Dengue, Zika, or Chikungunya by the end of the 11 th 8 week of 2019 in Brazil. This number represents almost three times the reported cases in 9 2018 for the same period [4]. These surveillance reports over time are essential in 10 providing scientific-based information to guide decision making, resources allocation, 11 and interventions [5]. The usage of mathematical models has demonstrated to be a 12 powerful tool in contributing to these data analysis [6-8]. One of the most significant 13 parameters extracted from these analyses is the basic reproduction number R o . R o is 14 defined as the number of secondary infections derived from one single infectious subject 15 and is widely used as an epidemiologic metric employed to describe the transmissibility 16 of infectious agents [9]. 17 Here we apply a compartmental mathematical model to investigate the dynamics of 18 Chikungunya outbreaks in the city of Rio de Janeiro in Brazil. The model consists of 19 ordinary differential equations that describe the transmission and the transition of the 20 diseases in humans and vectors [10, 11]. The model's parameters were extracted from 21 the literature or obtained from the best fit from the data of Rio de Janeiro surveillance 22 report for the years of 2016, 2018 and 2019 [12]. Based on these parameters, we estimate 23 the basic reproduction number R o for Chikungunya outbreaks in those years. We also 24 simulate a scenario predicting if the Mayaro virus could be a potential epidemic disease 25 in Rio de Janeiro. Modifications in the standard model equations were implemented to 26 introduce different possible ...