登革热流行的不规则性：首次和二次感染之间的差异比菌株的详细数量更能推动丰富的动态
Irregularity in dengue fever epidemics: difference between first and secondary infections drives the rich dynamics more than the detailed number of strains
摘要：
经典的单株SIR模型的主机人口的不同扩展，动机是模拟登革热流行病学，报告了丰富的动态结构，包括确定性混沌，能够解释疾病发病率的大幅波动。基本的两株登革热模型，它已经捕捉到原发性和继发性感染之间的差异，与四株登革热模型，在登革热流行病中引入多株竞争的想法之间的比较表明，第一次和继发性感染之间的差异驱动丰富的动态比在模型结构中考虑的菌株的详细数量。混沌动力学被发现发生在相同的参数区域的兴趣，两个和四个应变模型，能够解释在经验数据中观察到的波动，并显示出定性良好的经验数据和模型模拟之间的协议。由于简约法则倾向于两个竞争模型中最简单的一个，因此双应变模型将是更好的分析候选者，它给出了预期的复杂行为来解释经验数据中观察到的波动，并且确实是估计所有初始条件以及基于可用发病率数据的少数模型参数的更好选择。
英文摘要：
Different extensions of the classical single-strain SIR model for the host population, motivated by modeling dengue fever epidemiology, have reported a rich dynamic structure including deterministic chaos which was able to explain the large fluctuations of disease incidences. A comparison between the basic two-strain dengue model, which already captures differences between primary and secondary infections, with the four-strain dengue model, that introduces the idea of competition of multiple strains in dengue epidemics shows that the difference between first and secondary infections drives the rich dynamics more than the detailed number of strains to be considered in the model structure. Chaotic dynamics were found to happen at the same parameter region of interest, for both the two and the four-strain models, able to explain the fluctuations observed in empirical data and showing a qualitatively good agreement between empirical data and model simulation. Since the law of parsimony favors the simplest of two competing models, the two-strain model would be the better candidate to be analyzed, giving the expected complex behavior to explain the fluctuations observed in empirical data, and indeed the better option for estimating all initial conditions as well as the few model parameters based on the available incidence data.
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