COVID-19: Forecasting short term hospital needs in France

Massonnaud, Clément; Roux, Jonathan; Crépey, Pascal

doi:10.1101/2020.03.16.20036939

Cited by 87 publications

(100 citation statements)

References 19 publications

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“…And patients in areas with more than 5.5 health servicers per 1,000 population had shorter hospital stays. Massonnaud et al assessed COVID-19 impact on healthcare resources for each French metropolitan region based on the average length of stay in hospitals of 15 days, and showed that even in the best case scenario, the French healthcare system will very soon be overwhelmed 23 This paper shows the necessity of establishing a multi-level medical system and strengthening primary medical care, which can reduce the pressure of high-level hospitals in case of public health emergencies. In recent years, China has been strengthening the construction of lower-level medical systems and the monitoring of major diseases and health hazards, which deserve further implementation.…”

Section: Discussionmentioning

confidence: 98%

Survival analysis of hospital length of stay of novel coronavirus (COVID-19) pneumonia patients in Sichuan, China

wang

Liu

et al. 2020

Preprint

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Objective Allocation of medical resource is essential to a strong public health system in response to . Analysis of confirmed COVID-19 patients' hospital length of stay in Sichuan can be informative to decision-making in other regions of the world. Design A retrospective cross-sectional study. Data and Method Data from confirmed COVID-19 cases in Sichuan Province were obtained from the National Notifiable Diseases Reporting System (NNDRS) and field survey. We collected information on demographic, epidemiological, clinical characteristics, and the length of hospital stay for confirmed patients. We conducted an exploratory analysis using adjusted multivariate cox-proportional models. Participants A total of 538 confirmed patients of COVID-19 infection in Sichuan Province , 538 human cases of COVID-19 infection were laboratory-confirmed, and were hospitalized for treatment. Among these, 271 (50%) were 45 years of age or above, 285 (53%) were male, 450 (84%) were considered as having mild symptoms. The median hospital length of stay was 19 days (interquartile range (IQR): 14-23, Range: 3-41). Adjusted multivariate analysis showed that longer hospital length of stay was associated with factors aged 45 and over (HR: 0.74, 95% CI: 0.60-0.91), those admitted to provincial hospital (HR: 0.73, 95% CI: 0.54-0.99), and those with serious illness (HR: 0.66, 95% CI: 0.48-0.90); living in areas with more than 5.5 healthcare workers per 1000 population (HR: 1.32, 95% CI: 1.05-1.65) was associated with shorter hospital length of stay. There was no gender difference. Conclusions Preparation control measures of COVID-19 should involve the allocation of sufficient medical resources, especially in areas with older vulnerable populations and in areas that lack basic medical resources. Strengths and limitations of this studyPatients at least 45 years, those with serious illness, those living in areas with fewer healthcare workers per 1,000 people, and those admitted to higher levels of hospitalization had longer lengths of hospitalization, while gender, time interval from # Contributed equally.

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Section: Discussionmentioning

confidence: 98%

Survival analysis of hospital length of stay of novel coronavirus (COVID-19) pneumonia patients in Sichuan, China

wang

Liu

et al. 2020

Preprint

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“…Taking into account the latest information on the SARS-CoV-2 and its characteristics, namely regarding its transmission and its infectivity, the model used here is an enhanced version of our previous model developed to forecast hospital needs at the start of the epidemic in France. 5 The present model is composed of 8 compartments, whom 5 are dedicated to the infected phase, compared to 1 in a classic SEIR model. In more details, based on the knowledge on the transmission of the virus, we included two compartements (pre-symptomatic and asymptomatic) dedicated to cases without symptoms and being contagious.…”

Section: Discussionmentioning

confidence: 99%

COVID-19: One-month impact of the French lockdown on the epidemic burden

Roux

Massonnaud

Crépey

2020

Preprint

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104

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On March 16 2020, French authorities ordered a large scale lockdown to counter the COVID-19 epidemic wave rising in the country, stopping non-essential economic, educational, and entertainment activities, maintaining mainly food retailers and healthcare institutions. One month later, the number of new hospitalizations and ICU admissions had reached a plateau and were beginning a slow descent. We developed a spatialized, deterministic, age-structured, and compartmental SARS-CoV-2 transmission model able to reproduce the pre-lockdown dynamic of the epidemic in each of the 13 French metropolitan regions. Thanks to this model, we estimate, at regional and national levels, the total number of hospitalizations, ICU admissions, hospital beds requirements (hospitalization and ICU), and hospital deaths which may have been prevented by this massive and unprecedented intervention in France. If no control measures had been set up, between March 19 and April 19 2020, our analysis shows that almost 23% of the French population would have been affected by COVID-19 (14.8 million individuals). Hence, the French lockdown prevented 587,730 hospitalizations and 140,320 ICU admissions at the national level. The total number of ICU beds required to treat patients in critical conditions would have been 104,550, far higher than the maximum French ICU capacity. This first month of lockdown also permitted to avoid 61,739 hospital deaths, corresponding to a 83.5% reduction of the total number of predicted deaths. Our analysis shows that in absence of any control measures, the COVID-19 epidemic would have had a critical morbidity and mortality burden in France, overwhelming in a matter of weeks French hospital capacities.

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“…There have been numerous previous studies which have aimed to forecast the number of hospital beds required for COVID-19 patients [16][17][18][19][20][21][22]54]. Many of these studies published so far have used point estimates, only originating from one study which often does not reflect the context of interest.…”

Section: Summarising Length Of Staymentioning

confidence: 99%

COVID-19 length of hospital stay: a systematic review and data synthesis

Rees

Nightingale

Jafari

et al. 2020

Preprint

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Background: The COVID-19 pandemic has placed an unprecedented strain on health systems, with rapidly increasing demand for healthcare in hospitals and intensive care units (ICUs) worldwide. As the pandemic escalates, determining the resulting needs for healthcare resources (beds, staff, equipment) has become a key priority for many countries. Projecting future demand requires estimates of how long patients with COVID-19 need different levels of hospital care. Methods: We performed a systematic review to gather data on length of stay (LoS) of patients with COVID-19 in hospital and in ICU. We subsequently developed a method to generate LoS distributions which combines summary statistics reported in multiple studies, accounting for differences in sample sizes. Applying this approach we provide distributions for general hospital and ICU LoS from studies in China and elsewhere, for use by the community. Results: We identified 52 studies, the majority from China (46/52). Median hospital LoS ranged from 4 to 53 days within China, and 4 to 21 days outside of China, across 45 studies. ICU LoS was reported by eight studies -four each within and outside China -with median values ranging from 6 to 12 and 4 to 19 days, respectively. Our summary distributions have a median hospital LoS of 14 (IQR: 10-19) days for China, compared with 5 (IQR: 3-9) days outside of China. For ICU, the summary distributions are more similar (median (IQR) of 8 (5-13) days for China and 7 (4-11) days outside of China). There was a visible difference by discharge status, with patients who were discharged alive having longer LoS than those who died during their admission, but no trend associated with study date. Conclusion: Patients with COVID-19 in China appeared to remain in hospital for longer than elsewhere. This may be explained by differences in criteria for admission and discharge between countries, and different timing within the pandemic. In the absence of local data, the combined summary LoS distributions provided here can be used to model bed demands for contingency planning and then updated, with the novel method presented here, as more studies with aggregated statistics emerge outside China.

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COVID-19: Forecasting short term hospital needs in France

Cited by 87 publications

References 19 publications

Survival analysis of hospital length of stay of novel coronavirus (COVID-19) pneumonia patients in Sichuan, China

Survival analysis of hospital length of stay of novel coronavirus (COVID-19) pneumonia patients in Sichuan, China

COVID-19: One-month impact of the French lockdown on the epidemic burden

COVID-19 length of hospital stay: a systematic review and data synthesis

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