A dynamic analysis of tuberculosis dissemination to improve control and surveillance
Autor: | Ana Amador, Silvina Ponce Dawson, Wayner Vieira de Souza, Célio Lopes Silva, Antonio Ruffino-Netto, Carlos R. Zárate-Bladés, Rita Maria Zorzenon dos Santos, Maria Fatima P. M. de Albuquerque |
---|---|
Jazyk: | angličtina |
Rok vydání: | 2010 |
Předmět: |
Infectious Diseases/Epidemiology and Control of Infectious Diseases
Tuberculosis Process (engineering) Ciencias Físicas Control (management) Population Dynamics lcsh:Medicine Disease purl.org/becyt/ford/1 [https] Analisis espacio-temporal medicine Diseminacion de enfermedades contagiosas Humans lcsh:Science TRACE (psycholinguistics) Population Density Percolacion Multidisciplinary Geography Incidence Infectious Diseases/Respiratory Infections Principal (computer security) lcsh:R purl.org/becyt/ford/1.3 [https] medicine.disease Astronomía Identification (information) Risk analysis (engineering) Socioeconomic Factors Population Surveillance Public Health and Epidemiology/Preventive Medicine lcsh:Q Disease transmission Brazil Public Health and Epidemiology/Social and Behavioral Determinants of Health CIENCIAS NATURALES Y EXACTAS Research Article Infectious Diseases/Tropical and Travel-Associated Diseases |
Zdroj: | CONICET Digital (CONICET) Consejo Nacional de Investigaciones Científicas y Técnicas instacron:CONICET PLoS ONE PLoS ONE, Vol 5, Iss 11, p e14140 (2010) |
DOI: | 10.1371/journal.pone.0014140 |
Popis: | Background: Detailed analysis of the dynamic interactions among biological, environmental, social, and economic factors that favour the spread of certain diseases is extremely useful for designing effective control strategies. Diseases like tuberculosis that kills somebody every 15 seconds in the world, require methods that take into account the disease dynamics to design truly efficient control and surveillance strategies. The usual and well established statistical approaches provide insights into the cause-effect relationships that favour disease transmission but they only estimate risk areas, spatial or temporal trends. Here we introduce a novel approach that allows figuring out the dynamical behaviour of the disease spreading. This information can subsequently be used to validate mathematical models of the dissemination process from which the underlying mechanisms that are responsible for this spreading could be inferred. Methodology/Principal Findings: The method presented here is based on the analysis of the spread of tuberculosis in a Brazilian endemic city during five consecutive years. The detailed analysis of the spatio-temporal correlation of the yearly geo-referenced data, using different characteristic times of the disease evolution, allowed us to trace the temporal path of the aetiological agent, to locate the sources of infection, and to characterize the dynamics of disease spreading. Consequently, the method also allowed for the identification of socio-economic factors that influence the process. Conclusions/Significance: The information obtained can contribute to more effective budget allocation, drug distribution and recruitment of human skilled resources, as well as guiding the design of vaccination programs. We propose that this novel strategy can also be applied to the evaluation of other diseases as well as other social processes. © 2010 Zorzenon dos Santos et al. Fil: Zorzenon dos Santos, Rita M.. Universidade Federal de Pernambuco; Brasil Fil: Amador, Ana. Universidade Federal de Pernambuco; Brasil. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina Fil: de Souza, Wayner V.. Fundación Oswaldo Cruz; Brasil Fil: de Albuquerque, Maria Fatima P. M.. Universidade Federal de Pernambuco; Brasil. Fundación Oswaldo Cruz; Brasil Fil: Ponce Dawson, Silvina Martha. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina Fil: Ruffino-Netto, Antonio. Universidade de Sao Paulo; Brasil Fil: Zárate-Bladés, Carlos R.. Universidade de Sao Paulo; Brasil Fil: Silva, Celio L.. Universidade de Sao Paulo; Brasil |
Databáze: | OpenAIRE |
Externí odkaz: |
načítá se...