Modelling the SARS-CoVid-2 outbreak in Italy: development of a robust statistical index to track disease dynamics.

Bizzarri, Mariano; Traglia, Mario Di; Giuliani, Alessandro; Vestri, Annarita; Fedeli, Valeria; Prestininzi, Alberto

doi:10.21203/rs.3.rs-49880/v1

Cited by 3 publications

(2 citation statements)

References 4 publications

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“…Also, figure 2 shows that infectiousness increases as the number of outbreaks per inhabitant increases and the epidemic peak is earlier. This last result is expected and also predicted by mean field models like Verhulst-Pearle sigmoid [22] or SIR [23]. Such compartmental models have proven flexible, tractable, and highly informative as a general guide to the population-level behavior of diseases.…”

Section: Epidemic Spread On Social Network Under Quarantinesupporting

confidence: 62%

Optimising SARS-CoV-2 pooled testing strategies on social networks for low-resource settings

Mazzitello¹,

Jiang²,

Arizmendi³

2021

J. Phys. A: Math. Theor.

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Controlling the COVID-19 pandemic is an urgent global challenge. The rapid geographic spread of SARS-CoV-2 directly reflects the social structure. Before effective vaccines and treatments are widely available, we have to rely on alternative, non-pharmaceutical interventions, including frequent testing, contact tracing, social distancing, mask wearing, and hand-washing, as public health practises to slow down the spread of the disease. However, frequent testing is the key in the absence of any alternative. We propose a network approach to determine the optimal low resources setting oriented pool testing strategies that identifies infected individuals in a small number of tests and few rounds of testing, at low prevalence of the virus. We simulate stochastic infection curves on societies under quarantine. Allowing some social interaction is possible to keep the COVID-19 curve flat. However, similar results can be strategically obtained searching and isolating infected persons to preserve a healthier social structure. Here, we analyze which are the best strategies to contain the virus applying an algorithm that combine samples and testing them in groups [1]. A relevant parameter to keep infection curves flat using this algorithm is the daily frequency of testing at zones where a high infection rate is reported. On the other hand, the algorithm efficiency is low for random search of infected people.

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Section: Epidemic Spread On Social Network Under Quarantinesupporting

confidence: 62%

Optimising SARS-CoV-2 pooled testing strategies on social networks for low-resource settings

Mazzitello¹,

Jiang²,

Arizmendi³

2021

J. Phys. A: Math. Theor.

View full text Add to dashboard Cite

show abstract

“…Also, figure 2 shows that infectiousness increases as the number of outbreaks per inhabitant increases and the epidemic peak is earlier. This last result is expected and also predicted by mean field models like Verhulst-Pearle sigmoid [20] or SIR [21]. Such compartmental models have proven flexible, tractable, and highly informative as a general guide to the population-level behavior of diseases.…”

Section: Epidemic Spread On Social Network Under Quarantinesupporting

confidence: 62%

Optimising SARS-CoV-2 pooled testing strategies on social networks for low-resource settings

Mazzitello

Jiang

Arizmendi

2021

Preprint

View full text Add to dashboard Cite

Controlling the COVID-19 pandemic is an urgent global challenge. The rapid geographic spread of SARS-CoV-2 directly reflects the social structure. Before effective vaccines and treatments are widely available, we have to rely on alternative, non-pharmaceutical interventions, including frequency testing, contact tracing, social distancing, mask wearing, and hand-washing, as public health practises to slow down the spread of the disease. However frequent testing is the key in the absence of any alternative. We propose a network approach to determine the optimal low resources setting oriented pool testing strategies that identifies infected individuals in a small number of tests and few rounds of testing, at low prevalence of the virus. We simulate stochastic infection curves on societies under quarantine. Allowing some social interaction is possible to keep the COVID-19 curve flat. However, similar results can be strategically obtained searching and isolating infected persons to preserve a healthier social structure. Here, we analyze which are the best strategies to contain the virus applying an algorithm that combine samples and testing them in groups [1]. A relevant parameter to keep infection curves flat using this algorithm is the dairy frequency of testing at zones where a high infection rate is reported. On the other hand, the algorithm efficiency is low for random search of infected people.

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Epidemiological geography at work: An exploratory review about the overall findings of spatial analysis applied to the study of CoViD-19 propagation along the first pandemic year

2022

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The present work aims to give an overview on the international scientific papers related to the territorial spreading of SARS-CoV-2, with a specific focus upon applied quantitative geography and territorial analysis, to define a general structure for epidemiological geography research. The target publications were based on GIS spatial analysis, both in the sense of topological analysis and descriptive statistics or lato sensu geographical approaches. The first basic purpose was to organize and enhance the vast knowledge developments generated hitherto by the first pandemic that was studied “on-the-fly” all over the world. The consequent target was to investigate to what extent researchers in geography were able to draw scientifically consistent conclusions about the pandemic evolution, as well as whether wider generalizations could be reasonably claimed. This implied an analysis and a comparison of their findings. Finally, we tested what geographic approaches can say about the pandemic and whether a reliable spatial analysis routine for mapping infectious diseases could be extrapolated. We selected papers proposed for publication during 2020 and 209 articles complied with our parameters of query. The articles were divided in seven categories to enhance existing commonalities. In some cases, converging conclusions were extracted, and generalizations were derived. In other cases, contrasting or inconsistent findings were found, and possible explanations were provided. From the results of our survey, we extrapolated a routine for the production of epidemiological geography analyses, we highlighted the different steps of investigation that were attained, and we underlined the most critical nodes of the methodology. Our findings may help to point out what are the most critical conceptual challenges of epidemiological mapping, and where it might improve to engender informed conclusions and aware outcomes.

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Modelling the SARS-CoVid-2 outbreak in Italy: development of a robust statistical index to track disease dynamics.

Cited by 3 publications

References 4 publications

Optimising SARS-CoV-2 pooled testing strategies on social networks for low-resource settings

Optimising SARS-CoV-2 pooled testing strategies on social networks for low-resource settings

Optimising SARS-CoV-2 pooled testing strategies on social networks for low-resource settings

Epidemiological geography at work: An exploratory review about the overall findings of spatial analysis applied to the study of CoViD-19 propagation along the first pandemic year

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