Improving the Modeling of Disease Data from the Government Surveillance System: A Case Study on Malaria in the Brazilian Amazon

PLoS Computational Biology

Volumn 9, Issue 11, 2013, Pages

  Valle, Denis ^a   Clark, James ^b  

^a UNIVERSITY OF FLORIDA   (United States)

^b Duke University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

MONITORING;

BRAZILIAN AMAZON; CASE-STUDIES; DISEASE DYNAMICS; HUMAN DISEASE; LARGE-SCALES; MODELLING FRAMEWORK; SAMPLING EFFORTS; STATISTIC MODELING; SURVEILLANCE NETWORKS; SURVEILLANCE SYSTEMS;

DISEASES;

ARTICLE; BRAZIL; CASE STUDY; DISEASE MODEL; DISEASE SURVEILLANCE; EPIDEMIC; INCIDENCE; MALARIA; OBSERVATIONAL METHOD; PHENOMENOLOGY; POPULATION DYNAMICS; PREVALENCE; SIMULATION; STATISTICAL MODEL; SYMPTOMATOLOGY; TREND STUDY; VALIDATION PROCESS;

ALGORITHMS; BRAZIL; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; HUMANS; INCIDENCE; MALARIA; MARKOV CHAINS; MODELS, BIOLOGICAL; MONTE CARLO METHOD; PREVALENCE; PUBLIC HEALTH SURVEILLANCE; REPRODUCIBILITY OF RESULTS; SPATIAL ANALYSIS;

EID: 84888211586     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1003312     Document Type: Article

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