Fit and prediction of the average number of dengue cases for the selected neighborhoods in period , which starts in the 45th epidemiological week of 2015.

<p>Prediction for the 13th to 16th epidemiological weeks of 2018, city of Natal, RN. Solid line: Point adjustment/forecast. Gray region: Credibility interval at the 95% credibility level for the adjustment /forecast. Red dots: Reported dengue case counts.</p>

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Bibliographic Details
Main Author:	Mariane Branco Alves (21213504) (author)
Other Authors:	Rafael Santos Erbisti (21213507) (author), Aline Araújo Nobre (15310417) (author), Taynãna César Simões (8468688) (author), Alessandre de Medeiros Tavares (9667361) (author), Márcia Cristina Melo (21213510) (author), Rodrigo Moreira Pedreira (21213513) (author), Jan Pierre Martins de Araújo (21213516) (author), Marilia Sá Carvalho (9382230) (author), Nildimar Alves Honório (10833317) (author)
Published:	2025
Subjects:	Medicine Neuroscience Biotechnology Ecology Cancer Infectious Diseases Virology Computational Biology Environmental Sciences not elsewhere classified endemic northeast city egg positivity index consider simultaneous variability bayesian spatiotemporal learning subsequent four weeks prior four weeks next four weeks areas consistently exhibiting support timely interventions optimal model revealed arboviruses like dengue identifying priority areas aedes aegypti </ proposed bayesian space egg density index weekly risk dynamics persistent dengue risk forecasting dengue cases brazil </ p dengue occurrence probability priority areas aedes </ several weeks dengue cases transmission dynamics predictive model dengue occurrence increased cases cases across zero periods zero occurrences timely identification time provides time analysis temporally heterogeneous statistical models spatial dependence significant rise rio grande remained concentrated realistic estimates previous week predictors included predictive maps offset term observation week intervention focused fitted using expected number epidemiological week
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Fit and prediction of the average number of dengue cases for the selected neighborhoods in period , which starts in the 45th epidemiological week of 2015.

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