The 2020 SARS-CoV-2 epidemic in England: key epidemiological drivers and impact of interventions

Knock, Edward; Whittles, Lilith K; Lees, John A.; Perez‐Guzman, Pablo N; Verity, Robert; FitzJohn, Richard G.; Gaythorpe, Katy A. M.; Imai, Natsuko; Hinsley, Wes; Okell, Lucy; Roselló, Alicia; Kantas, Nikolas; Walters, Caroline E.; Bhatia, Sangeeta; Watson, Oliver J; Whittaker, C; Cattarino, Lorenzo; Boonyasiri, Adhiratha; Djaafara, Bimandra A; Fraser, Keith; Fu, Han; Wang, Haowei; Xi, Xiaoyue; Donnelly, Christl A.; Jauneikaite, Elita; Laydon, Daniel J.; White, Peter J; Ghani, Azra C; Ferguson, Neil; Cori, Anne; Baguelin, Marc

doi:10.1101/2021.01.11.21249564

Cited by 28 publications

(121 citation statements)

References 42 publications

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“…One possible explanation for this is a higher proportion of time spent indoors in colder months leading to an increased household transmission risk, particularly in the early stages of infection before symptoms develop (since symptomatic infected hosts are still likely to self-isolate). While shorter generation times may in general be over-represented in data collected from infector-infectee pairs at times when case numbers are rising [8,26,38] (as was the case in September and October [39,40]), we estimated the mean generation time to be similar in November (when national case numbers were mostly decreasing [39,40]) compared to September and October (Figure S7).…”

Section: Discussionmentioning

confidence: 99%

Inference of SARS-CoV-2 generation times using UK household data

Hart

Abbott

Endo

et al. 2021

Preprint

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The distribution of the generation time (the interval between individuals becoming infected and passing on the virus) characterises changes in the transmission risk during SARS-CoV-2 infections. Inferring the generation time distribution is essential to plan and assess public health measures. We previously developed a mechanistic approach for estimating the generation time, which provided an improved fit to SARS-CoV-2 data from January-March 2020 compared to existing models. However, few estimates of the generation time exist based on data from later in the pandemic. Here, using data from a household study conducted from March-November 2020 in the UK, we provide updated estimates of the generation time. We consider both a commonly used approach in which the transmission risk is assumed to be independent of when symptoms develop, and our mechanistic model in which transmission and symptoms are linked explicitly. Assuming independent transmission and symptoms, we estimated a mean generation time (4.2 days, 95% CrI 3.3-5.3 days) similar to previous estimates from other countries, but with a higher standard deviation (4.9 days, 3.0-8.3 days). Using our mechanistic approach, we estimated a longer mean generation time (6.0 days, 5.2-7.0 days) and a similar standard deviation (4.9 days, 4.0-6.3 days). Both models suggest a shorter mean generation time in September-November 2020 compared to earlier months. Since the SARS-CoV-2 generation time appears to be changing, continued data collection and analysis is necessary to inform future public health policy decisions.

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Section: Discussionmentioning

confidence: 99%

Inference of SARS-CoV-2 generation times using UK household data

Hart

Abbott

Endo

et al. 2021

Preprint

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“…Large numbers of asymptomatic and mildly symptomatic cases 17 , as well as difficulties with testing, particularly in the United States 18 , left policymakers with substantial uncertainty regarding the virus's epidemiological parameters and the case numbers in many locations. Countries including the United States and United Kingdom waited to intervene until transmission was widespread; retrospective analyses later claimed that even slightly earlier intervention would have saved many lives 19,20 .…”

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confidence: 99%

Optimal, near-optimal, and robust epidemic control

et al. 2021

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In the absence of drugs and vaccines, policymakers use non-pharmaceutical interventions such as social distancing to decrease rates of disease-causing contact, with the aim of reducing or delaying the epidemic peak. These measures carry social and economic costs, so societies may be unable to maintain them for more than a short period of time. Intervention policy design often relies on numerical simulations of epidemic models, but comparing policies and assessing their robustness demands clear principles that apply across strategies. Here we derive the theoretically optimal strategy for using a time-limited intervention to reduce the peak prevalence of a novel disease in the classic Susceptible-Infectious-Recovered epidemic model. We show that broad classes of easier-to-implement strategies can perform nearly as well as the theoretically optimal strategy. But neither the optimal strategy nor any of these near-optimal strategies is robust to implementation error: small errors in timing the intervention produce large increases in peak prevalence. Our results reveal fundamental principles of non-pharmaceutical disease control and expose their potential fragility. For robust control, an intervention must be strong, early, and ideally sustained.

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“…Evidence suggests that the effects of COVID-19 on care homes have been closely linked to the prevalence of COVID-19 in the community. 220,224,225,226 This means that the wider policy response to COVID-19 -for example, the effectiveness of lockdowns and testing systems -shapes the ability to protect adult social care services and staff. Changes to policy and practice at a local level -by local authorities, health and care systems, and care providers -have also impacted the protection afforded to people in social care.…”

Section: Discussionmentioning

confidence: 99%

Adult social care and COVID-19 after the first wave

Alderwick¹,

Dunn²,

Allen³

et al. 2021

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A key question for any future inquiry into the government's handling of COVID-19 will be how well government protected people using and providing adult social care.• COVID-19 has had a major and sustained impact on social care in England. There have been 27,179 excess deaths among care home residents in England since 14 March 2020 (a 20% increase compared with recent years), and 9,571 excess deaths reported among people receiving domiciliary care since 11 April 2020 (a 62% increase). Social care staff have been at higher risk of dying from COVID-19 than others of the same age and sex. The wider health impacts -from reduced access to care, social isolation, increased burden on carers -are harder to measure but also significant. •The policy response to COVID-19 is complex and evolving. Challenges in protecting people who use and provide social care during the pandemic have not been unique to England. The task of protecting social care is closely tied to the broader task of protecting the population from COVID-19.• During the first wave of the pandemic, central government support for social care in England was too slow and limited, leading to inadequate protection for people using and providing care. In this briefing, we analysed national government policy on adult social care in England after the first wave of COVID-19 -between June 2020 and March 2021.• Overall, we found a mixed picture. Support in some areas improved, such as access to testing and PPE, and the priority given to social care appeared to increase. Groups using and providing social care were prioritised for COVID-19 vaccines, alongside the NHS. This is likely to have offered much greater protection to care home residents and others.Briefing: Adult social care and COVID-19 after the first wave 2 •Major structural issues in social care have shaped the policy response and effects of COVID-19 on the sector. These include chronic underfunding, workforce issues, system fragmentation, and more. COVID-19 also appears to have made some longstanding problems worse, such as unmet need for care and the burden on unpaid carers. The longstanding political neglect of social care in England has been laid bare for all to see. Continued neglect would leave the system vulnerable to future shocks.• Fundamental reform of adult social care in England is needed to address the longstanding policy failures exposed by COVID-19. This reform must be comprehensive and long-term -not narrowly focused on preventing older people selling their homes to pay for care. Immediate policy action and investment is also needed to support the system to recover from the pandemic and prepare for potential future waves of COVID-19.* For excess deaths among care home residents, we compared deaths to the 5-year average (2015)(2016)(2017)(2018)(2019). For excess deaths among people receiving domiciliary care, this was compared to the 3-year average (2017)(2018)(2019). † The number of excess deaths for the whole period (since the start of the pandemic) is lower than the number of excess deaths in t...

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The 2020 SARS-CoV-2 epidemic in England: key epidemiological drivers and impact of interventions

Cited by 28 publications

References 42 publications

Inference of SARS-CoV-2 generation times using UK household data

Inference of SARS-CoV-2 generation times using UK household data

Optimal, near-optimal, and robust epidemic control

Adult social care and COVID-19 after the first wave

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