Modeling Impact of Temperature and Human Movement on the Persistence of Dengue Disease

Abstract

Dengue is a vector-borne infectious disease endemic in many parts of the world. The disease is spreading in new places due to human movement into the dengue disease supporting areas. Temperature is the major climatic factor which affects the biological processes of the mosquitoes and their interaction with the viruses. In the present work, we propose a multipatch model to assess the impact of temperature and human movement in the transmission dynamics of dengue disease. The work consists of system of ordinary differential equations that describe the transmission dynamics of dengue disease between humans and mosquitoes. Human population is divided into four classes: susceptible, exposed, infectious, and recovered. Mosquito population is divided into three classes: susceptible, exposed, and infectious. Basic reproduction number ℛ0 of the model is obtained using Next-Generation Matrix method. The qualitative analysis of the model is made in terms of the basic reproduction number. Parameters used in the model are considered temperature dependent. Dynamics of vector and host populations are investigated with different human movement rates and different temperature levels. Numerical results show that proper management of human movement between patches helps reducing the burden of dengue disease. It is also seen that the temperature affects the transmission dynamics of the disease significantly.

Population Movement, City Closure in Wuhan, and Geographical Expansion of the COVID-19 Infection in China in January 2020

“…c c e p t e d M a n u s c r i p t 14 consistent with those of other coronavirus studies[15][16][17]. Since the virus is transmitted through the respiratory tract and close contact, the infection is greatly affected by population movements: a great number of people flowing out of Wuhan may transmit the virus to other parts of China during the Chinese Spring Festival, and the absence of detectable symptoms during the long incubation period made it difficult to identify cases in the early stage[18], which made the 2019-ncov virus be able to spread on a large scale in a short period of time.…”

A Framework for Weather-Driven Dengue Virus Transmission Dynamics in Different Brazilian Regions

“…Here, we used temperature and rainfall time series derived from weather satellite data. Other works in the literature usually employ sinusoidal functions to represent temperature variations [ 7 , 50 , 52 , 53 ] or constant temperature [ 24 , 54 , 55 ]. Our model was capable of producing similar patterns to those observed for dengue incidence, presenting both seasonality and similar epidemic sizes.…”

Clustered Breeding Sites: Shelters for Vector-Borne Diseases

“…Our simulations suggest that vector-control programmes should take into consideration the spatial distribution of vectors and not only the disease prevalence and/or the vector population size. A decrease in the number of infections can also be achieved by restricting the mobility of the host population in the infected region [ 9 , 11 , 14 , 19 ], but this surveillance measure may be difficult to implement in practice.…”

“…In many models, the vector population is divided into infected and noninfected subgroups [ 7 – 9 , 11 – 14 , 19 , 20 ]. In our model, this division is not made; only the vector abundance matters.…”