How mathematical modelling can inform outbreak response vaccination

BMC Infectious Diseases, Journal Year: 2024, Volume and Issue: 24(1)

Published: Dec. 1, 2024

Abstract Mathematical models are established tools to assist in outbreak response. They help characterise complex patterns disease spread, simulate control options public health authorities decision-making, and longer-term operational financial planning. In the context of vaccine-preventable diseases (VPDs), vaccines one most-cost effective response interventions, with potential avert significant morbidity mortality through timely delivery. Models can contribute design vaccine by investigating importance timeliness, identifying high-risk areas, prioritising use limited supply, highlighting surveillance gaps reporting, determining short- long-term benefits. this review, we examine how have been used inform for 10 VPDs, provide additional insights into challenges modelling, such as data gaps, key vaccine-specific considerations, communication between modellers stakeholders. We illustrate that while policy-oriented response, they only be good them.

Language: Английский

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Geosocial Media’s Early Warning Capabilities Across US County-Level Political Clusters: Observational Study (Preprint)

Published: March 19, 2024

The novel coronavirus disease (COVID-19) sparked significant health concerns worldwide, prompting policy makers and care experts to implement nonpharmaceutical public interventions, such as stay-at-home orders mask mandates, slow the spread of virus. While these interventions proved essential in controlling transmission, they also caused substantial economic societal costs should therefore be used strategically, particularly when activity is on rise. In this context, geosocial media posts (posts with an explicit georeference) have been shown provide a promising tool for anticipating moments potential crises. However, previous studies early warning capabilities data largely constrained by coarse spatial resolutions or short temporal scopes, limited understanding how local political beliefs may influence capabilities. This study aimed assess epidemiological COVID-19 vary over time across US counties differing beliefs. We classified into 3 clusters, democrat, republican, swing counties, based voting from last 6 federal election cycles. we analyzed consecutive waves (February 2020-April 2022). specifically examined lag between signals surges cases, measuring both number days which preceded cases (temporal lag) correlation their respective series. differed clusters waves. On average, 21 republican compared 14.6 democrat 24.2 counties. general, were preceding 5 out all clusters. observed decrease that Furthermore, decline signal strength impact trending topics presented challenges reliability signals. provides valuable insights strengths limitations tool, highlighting can change county-level Thus, findings indicate future systems might benefit accounting addition, declining role need assessed research.

Language: Английский

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Adaptive metrics for an evolving pandemic: A dynamic approach to area-level COVID-19 risk designations

Proceedings of the National Academy of Sciences, Journal Year: 2023, Volume and Issue: 120(32)

Published: Aug. 1, 2023

Throughout the COVID-19 pandemic, policymakers have proposed risk metrics, such as CDC Community Levels, to guide local and state decision-making. However, metrics not reliably predicted key outcomes often lacked transparency in terms of prioritization false-positive versus false-negative signals. They also struggled maintain relevance over time due slow infrequent updates addressing new variants shifts vaccine- infection-induced immunity. We make two contributions address these weaknesses. first present a framework evaluate predictive accuracy based on policy targets related severe disease mortality, allowing for explicit preferences toward This approach allows optimize specific interventions. Second, we propose method update thresholds real time. show that this adaptive designating areas “high risk” improves performance static predicting 3-wk-ahead mortality intensive care usage at both county levels. demonstrate with our approach, using only hospital admissions predict has performed consistently well include cases inpatient bed usage. Our results highlight challenge prediction is changing relationship between indicators interest. Adaptive therefore unique advantage rapidly evolving pandemic context.

Language: Английский

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An integrated infoveillance approach using google trends and Talkwalker: Listening to web concerns about COVID-19 vaccines in Italy

Healthcare Analytics, Journal Year: 2023, Volume and Issue: 4, P. 100272 - 100272

Published: Oct. 7, 2023

Language: Английский

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Governmental Anti-Covid Measures Effectiveness Detection

Procedia Computer Science, Journal Year: 2023, Volume and Issue: 225, P. 2922 - 2931

Published: Jan. 1, 2023

We present a retrospective analysis of Czech anti-covid governmental measures’ effectiveness for an unusually long three years observation. Numerous government restrictive measures illustrate this applied to COVID-19 data from the first cases detected on 1st March 2020 till 2023. It illustrates course dramatic combat unknown illness resignation country-wide and placing into category common nuisances. Our uses derived adaptive recursive Bayesian stochastic multidimensional Covid model-based prediction nine essential publicly available series. The model enables us differentiate between effective solely nuisance or antagonistic provisions their correct wrong timing. COVID allows predict vital covid statistics such as number hospitalized, deaths, symptomatic individuals, which can serve daily control necessary precautions formulate recommendations future pandemics.

Language: Английский

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