Nowcasting (Short-Term Forecasting) of COVID-19 Hospitalizations Using Syndromic Healthcare Data, Sweden, 2020

Spreco, Armin; Jöud, Anna; Eriksson, Olle; Soltesz, Kristian; Källström, Reidar; Dahlström, Örjan; Eriksson, Henrik; Ekberg, Joakim; Jonson, Carl‐Oscar; Fraenkel, Carl-Johan; Lundh, Torbjörn; Gerlee, Philip; Gustafsson, Fredrik; Timpka, Toomas

doi:10.3201/eid2803.210267

Cited by 11 publications

(5 citation statements)

References 35 publications

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“…The increase of SARS-CoV-2 RNA in wastewater coincided or preceded with approximately 1-2 weeks an increase in the number of urgent calls to 1177 Va ˚rdguiden regarding breathing difficulties in adults. In another study from Sweden, it was shown that an increase in the number of urgent calls to 1177 preceded an increase in the number of hospitalized patients with about one to two weeks at the beginning of the pandemic (Spreco et al, 2022), as was shown also in this study. These results indicate that monitoring of viruses in wastewater could also predict an upcoming burden for the emergency medical communication centers, responsible for coordinating transports of patients and patient samples.…”

Section: Discussionsupporting

confidence: 87%

The amount of SARS-CoV-2 RNA in wastewater relates to the development of the pandemic and its burden on the health system

et al. 2022

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Section: Discussionsupporting

confidence: 87%

The amount of SARS-CoV-2 RNA in wastewater relates to the development of the pandemic and its burden on the health system

et al. 2022

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“…In summary, the discrepancy between hospitalization and ICU patient data and model results can be attributed to various factors, mainly related to wave magnitude rather than peak or length. This result highlights the importance of considering data collection and nowcasting issues when interpreting modeling results [50][51][52].…”

Section: Discussionmentioning

confidence: 90%

A Deep Dive into the Delta Wave: Forecasting SARS-CoV-2 Epidemic Dynamic in Poland with the pDyn Agent-Based Model

Niedzielewski,

Bartczuk,

Bielczyk

et al. 2023

Preprint

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In this work, we describe and forecast the fourth wave of the SARS-CoV-2 epidemic, driven by the Delta variant, using pDyn — a detailed epidemiological agent-based model. It is designed to explain the spatiotemporal dynamics of the SARS-CoV-2 spread across Polish society, predicting the number and locations of disease-related states for agents living in the virtual society in response to varying properties of the pathogen and the social structure and behavior. We evaluate the validity of the dynamics generated by the model, including the succession of pathogen variants, immunization dynamics, and the ratio of vaccinated individuals among confirmed cases. Additionally, we assess the model’s predictive power in estimating pandemic dynamics (peak timing, peak value, and wave length) of disease-related states (number of confirmed cases, hospitalizations, ICU hospitalizations, and deaths) both at the national level and in the highest administrative units in Poland (voivodships). When testing the model’s validity, we compared real-world data (excluding data used for calibration) to our model estimates to evaluate whether pDyn accurately reproduced the epidemic dynamics up to the simulation time (October 28, 2021). To assess the accuracy of pDyn’s predictions, we retrospectively compared simulation results with real-world data acquired after the simulation date, evaluating pDyn as a tool for predicting future epidemic spread. Our results indicate that pDyn accurately predicts and can help us better understand the mechanisms underlying the SARS-CoV-2 dynamics.

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“…Monitoring R t , the average number of secondary cases caused by a single infected individual in a large population, during an outbreak is useful for assessing transmission dynamics and evaluating the effectiveness of public health measures (e.g., vaccination, contact tracing, isolation, and quarantine) (Cori et al, 2013). Nowcasts and forecasts were produced by numerous research groups around the globe (Arslan et al, 2021;Birrell et al, 2021;Cramer et al, 2022;Spreco et al, 2022), the results of which were instrumental for decision makers weighing possible control measures (Biggerstaff et al, 2021) such as lockdowns and social distancing. Outbreak forecasting predicts specific outcomes, (e.g., number of cases, deaths, or hospitalizations) at some specific future times (e.g., weeks, months, etc.…”

Section: W I T H D R a W Nmentioning

confidence: 99%

Nowcasting and Forecasting the 2022 U.S. Mpox Outbreak: Support for Public Health Decision Making and Lessons Learned

Charniga

Madewell

Masters

et al. 2023

Preprint

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Mpox is a zoonotic disease endemic in Central and West Africa. In May 2022, an outbreak of mpox characterized by human-to-human transmission was detected in multiple non-endemic countries. We performed nowcasting and forecasting for the 2022 mpox outbreak in the United States using the R package EpiNow2. We generated nowcasts/forecasts at the national level, by Census region, and for jurisdictions reporting the greatest number of mpox cases. Modeling results were shared for situational awareness within the Centers for Disease Control and Prevention (CDC) Mpox Response and publicly on the CDC website. We retrospectively evaluated forecast predictions at four key phases during the outbreak using three metrics, the weighted interval score, mean absolute error, and prediction interval coverage. We compared the performance of EpiNow2 with a naive Bayesian generalized linear model (GLM). The EpiNow2 model had less probabilistic error than the GLM during every outbreak phase except for the early phase. We share our experiences with an existing tool for nowcasting/forecasting and highlight areas of improvement for the development of future tools. We also reflect on lessons learned regarding data quality issues and adapting modeling results for different audiences.

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Nowcasting (Short-Term Forecasting) of COVID-19 Hospitalizations Using Syndromic Healthcare Data, Sweden, 2020

Cited by 11 publications

References 35 publications

The amount of SARS-CoV-2 RNA in wastewater relates to the development of the pandemic and its burden on the health system

The amount of SARS-CoV-2 RNA in wastewater relates to the development of the pandemic and its burden on the health system

A Deep Dive into the Delta Wave: Forecasting SARS-CoV-2 Epidemic Dynamic in Poland with the pDyn Agent-Based Model

Nowcasting and Forecasting the 2022 U.S. Mpox Outbreak: Support for Public Health Decision Making and Lessons Learned

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