Departamento de Física, Universidade Federal de Pernambuco, Cidade Universitária, Recife, Pernambuco, Brazil.
PLoS One. 2010 Nov 30;5(11):e14140. doi: 10.1371/journal.pone.0014140.
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.
详细分析有利于某些疾病传播的生物、环境、社会和经济因素之间的动态相互作用，对于设计有效的控制策略非常有用。像结核病这样的疾病，每 15 秒钟就会在世界上夺走一个人的生命，需要考虑到疾病动态的方法来设计真正有效的控制和监测策略。常用的和成熟的统计方法提供了对有利于疾病传播的因果关系的深入了解，但它们只能估计风险区域、时空趋势。在这里，我们介绍了一种新的方法，可以确定疾病传播的动态行为。这些信息随后可用于验证传播过程的数学模型，从中可以推断出导致这种传播的潜在机制。
方法/主要发现：这里提出的方法基于对巴西一个地方性城市五年间结核病传播的分析。使用疾病演化的不同特征时间，对每年地理参考数据的时空相关性进行详细分析，使我们能够追踪病因的时间路径、确定感染源，并描述疾病传播的动态。因此，该方法还能够识别影响该过程的社会经济因素。
结论/意义：获得的信息有助于更有效地分配预算、分配药物和招募有技能的人力资源，并指导疫苗接种计划的设计。我们提出，这种新策略也可以应用于评估其他疾病以及其他社会进程。
