Modeling the dynamic transmission of dengue fever: investigating disease persistence.
BACKGROUND
Dengue is a disease of great complexity, due to interactions between humans, mosquitoes and various virus serotypes as well as efficient vector survival strategies. Thus, understanding the factors influencing the persistence of the disease has been a challenge for scientists and policy makers. The aim of this study is to investigate the influence of various factors related to humans and vectors in the maintenance of viral transmission during extended periods.


RESULTS
We developed a stochastic cellular automata model to simulate the spread of dengue fever in a dense community. Each cell can correspond to a built area, and human and mosquito populations are individually monitored during the simulations. Human mobility and renewal, as well as vector infestation, are taken into consideration. To investigate the factors influencing the maintenance of viral circulation, two sets of simulations were performed: (1(st)) varying human renewal rates and human population sizes and (2(nd)) varying the house index (fraction of infested buildings) and vector per human ratio. We found that viral transmission is inhibited with the combination of small human populations with low renewal rates. It is also shown that maintenance of viral circulation for extended periods is possible at low values of house index. Based on the results of the model and on a study conducted in the city of Recife, Brazil, which associates vector infestation with Aedes aegytpi egg counts, we question the current methodology used in calculating the house index, based on larval survey.


CONCLUSIONS
This study contributed to a better understanding of the dynamics of dengue subsistence. Using basic concepts of metapopulations, we concluded that low infestation rates in a few neighborhoods ensure the persistence of dengue in large cities and suggested that better strategies should be implemented to obtain measures of house index values, in order to improve the dengue monitoring and control system.
Centro de Ciência do Sistema Terrestre, Instituto Nacional de Pesquisas Espaciais, INPE, São José dos Campos, Brazil. liliam.castro@inpe.br
Líliam César
LC
de Castro Medeiros
César Augusto Rodrigues
CA
Castilho
Cynthia
C
Braga
Wayner Vieira
WV
de Souza
Leda
L
Regis
Antonio Miguel Vieira
AM
Monteiro
D000330:Aedes / Q000254:growth & development* / Q000821:virology*; D000818:Animals; D001938:Brazil / Q000453:epidemiology; D002947:Cities; D003715:Dengue / Q000453:epidemiology* / Q000635:transmission*; D005260:Female; D006801:Humans; D007303:Insect Vectors / Q000254:growth & development* / Q000821:virology*; D015233:Models, Statistical; D011156:Population Density; D011157:Population Dynamics
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