Dataset Information

Societal heterogeneity contributes to complex dynamic patterns of the COVID-19 pandemics: insights from a novel Stochastic Heterogeneous Epidemic Model (SHEM).

ABSTRACT: After months of COVID-19 quarantine, businesses are reopening their doors and people are reentering society. Within the current COVID-19 data, after a slow-down of infection, a new peak in active cases is already forming. Here we developed a new Stochastic Heterogeneous Epidemic Model (SHEM) to investigate genesis of complex pandemic patterns with the focus on the role of heterogenous societal structure. Using this model with R0 of COVID-19, we simulated viral infection in different scenarios where isolated, communities surround the main cluster of the population. Depending on the parameters of heterogeneity and isolation period, our simulations generated a multimodal growth periods with multiple peaks, an extended plateau, a prolonged tail, or a delayed second wave of infection. We show that timing and magnitude of infection for previously unaffected isolated clusters of people, such as suburban neighborhoods, are critical aspects of these patterns. Our model can be applied to communities at any given scale of population described as a fractal-like structure, i.e. from the entire human population, to a country, down to a province or city levels with relevant societal heterogeneity structure. The current COVID-19 pandemic development worldwide and in the US follows a bimodal rise pattern, qualitatively similar to that in our simulations. We interpret our data to indicate that the secondary peak in the pattern is contributed by the states and counties in the US with late infection surges that are analogous to isolated suburbs in our model. Furthermore, the on-going early reopening, i.e. premature partial reopening in our model, is further accelerating the peak rise. This peak now reaches new heights, forcing many states in the US to reverse their policies and reestablish their quarantine measures. Our results support these timely and effective measures: we show that longer quarantine periods can reduce the number of deaths and transform the current trend into a substantially delayed (>1 year) second wave. If this scenario becomes a reality, it is important (i) to develop the vaccine and/or effective treatment before the second wave; (ii) to warn people living in suburbs that it is these isolated areas that may hold a false sense of security, but they should continue to take extra care for their public health.

SUBMITTER: Maltsev AV

PROVIDER: S-EPMC7359544 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Social heterogeneity drives complex patterns of the COVID-19 pandemic: insights from a novel Stochastic Heterogeneous Epidemic Model (SHEM).

Maltsev Alexander V AV Stern Michael D MD

medRxiv : the preprint server for health sciences 20201130

In todays absence of a vaccine and impactful treatments, the most effective way to combat the virus is to find and implement mitigation strategies. An invaluable resource in this task is numerical modeling that can reveal key factors in COVID-19 pandemic development. On the other hand, it has become evident that regional infection curves of COVID-19 exhibit complex patterns which often differ from curves predicted by forecasting models. The wide variations in attack rate observed among different ...[more]

PMID: 32676619

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Project description:Stellate cells (SC) in the medial entorhinal cortex manifest intrinsic membrane potential oscillatory patterns. Although different theoretical frameworks have been proposed to explain these patterns, a robust unifying framework that jointly accounts for intrinsic heterogeneities and stochasticity is missing. Here, we first performed in vitro patch-clamp electrophysiological recordings from rat SCs and found pronounced cell-to-cell variability in their characteristic physiological properties, including peri-threshold oscillatory patterns. We demonstrate that noise introduced into two independent populations (endowed with deterministic or stochastic ion-channel gating kinetics) of heterogeneous biophysical models yielded activity patterns that were qualitatively similar to electrophysiological peri-threshold oscillatory activity in SCs. We developed spectrogram-based quantitative metrics for the identification of valid oscillations and confirmed that these metrics reliably captured the variable-amplitude and arhythmic oscillatory patterns observed in electrophysiological recordings. Using these quantitative metrics, we validated activity patterns from both heterogeneous populations of SC models, with each model assessed with multiple trials of different levels of noise at distinct membrane depolarizations. Our analyses unveiled the manifestation of stochastic resonance (detection of the highest number of valid oscillatory traces at an optimal level of noise) in both heterogeneous populations of SC models. Finally, we show that a generalized network motif comprised of a slow negative feedback loop amplified by a fast positive feedback loop manifested stochastic bifurcations and stochastic resonance in the emergence of oscillations. Together, through a unique convergence of the degeneracy and stochastic resonance frameworks, our unifying framework centered on heterogeneous stochastic bifurcations argues for state-dependent emergence of SC oscillations.

Dataset Information

Societal heterogeneity contributes to complex dynamic patterns of the COVID-19 pandemics: insights from a novel Stochastic Heterogeneous Epidemic Model (SHEM).

Publications

Social heterogeneity drives complex patterns of the COVID-19 pandemic: insights from a novel Stochastic Heterogeneous Epidemic Model (SHEM).

Similar Datasets

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