Fitting the Incidence Data from the City of Campinas, Brazil, Based on Dengue Transmission Modellings Considering Time-Dependent Entomological Parameters

Abstract

Four time-dependent dengue transmission models are considered in order to fit the incidence data from the City of Campinas, Brazil, recorded from October 1st 1995 to September 30th 2012. The entomological parameters are allowed to depend on temperature and precipitation, while the carrying capacity and the hatching of eggs depend only on precipitation. The whole period of incidence of dengue is split into four periods, due to the fact that the model is formulated considering the circulation of only one serotype. Dengue transmission parameters from human to mosquito and mosquito to human are fitted for each one of the periods. The time varying partial and overall effective reproduction numbers are obtained to explain the incidence of dengue provided by the models.

Mathematical model describing CoViD-19 in São Paulo State, Brazil – Evaluating isolation as control mechanism and forecasting epidemiological scenarios of release

“…However, if we increase the proportion of isolated persons above 80%, then the health care system can treat well all patients during the first wave. Let us evaluate the occupancy of beds in hospitals and ICU, using equations (16) and (17). We let h 1 = h 1y = h 1o = 1, h = h y = h o = 0.3, ς 1 = 1/14 (2 weeks of hospital care), and ς 2 = 1/21 (3 weeks of ICU care) [3].…”

Seasonal temperature variation influences climate suitability for dengue, chikungunya, and Zika transmission

“…Here, we expand on previous work with three main advances: (1) we incorporate the full suite of empirically-derived, unimodal thermal responses for all known transmission-relevant mosquito and parasite traits; (2) we examine the influence of seasonal temperature mean and variation (in contrast to constant temperatures or daily temperature variation); and (3) we use a dynamic transmission framework to explore the impact of different seasonal temperature regimes on the epidemiologically-relevant outcomes of epidemic size, duration, and peak incidence (in contrast to R0, or vectorial capacity, which are difficult to measure directly). To do so, we incorporate previously estimated and independently validated thermal response functions for all vector and parasite traits [24] into a dynamic SEI-SEIR model [25,26]. We explore field-relevant temperature regimes by simulating epidemics across temperature means (10 – 38°C) and seasonal ranges (0 – 17°C) from across the predicted suitable range for transmission.…”

Arbovirus Vectors of Epidemiological Concern in the Americas: A Scoping Review of Entomological Studies on Zika, Dengue and Chikungunya Virus Vectors

“…Rojas et al [185] found attack rates in Girardot and San Andres, Colombia to be highest among females, aged 20-49. Three studies reported that meteorological variables including temperature and humidity are important determinants of transmission dynamics [186,187,189,190], and one study found that transovarial transmission plays an important role in transmission dynamics depending on basic reproductive number [188]. Liu-Helmersson et al [107] predicted an increase in diurnal temperature range and increased dengue epidemic potential under climate changes in cold, temperate and extremely hot climates where mean temperatures are far from 29 °C.…”