The hottest Epidemiology Substack posts right now

As vaccination rates increase, the need for rapid screening to prevent outbreaks remains crucial because both vaccines and screening can help control the spread of Covid-19.
The effectiveness of rapid screening in reducing the risk of outbreaks significantly increases as the percentage of vaccinated individuals rises, highlighting the importance of combining vaccination with screening.
There is a potential issue of waning immunity post-vaccination, especially among older populations, which could lead to the re-emergence of Covid-19. This emphasizes the need for a surveillance plan to monitor immunity levels in the vaccinated population and address any possible resurgence.

Targeting reproduction numbers (R) in epidemics is common, but focusing on the average R can be misleading because individual variances matter.
Policies like lockdowns and screening programs can be more effective in reducing both average R and its variance, making them reliable indicators of success.
Understanding how policies impact the variance of R is crucial to ensuring sustained mitigation of outbreaks and keeping case numbers down.

A large-scale Covid-19 testing experiment was conducted in Liverpool using a combination of PCR and rapid antigen tests, impacting almost 500,000 people.
Confirmatory PCR tests for positive rapid test results had poor uptake, highlighting challenges in ensuring follow-up testing.
The quality of rapid tests varied, emphasizing the importance of recording and evaluating batch and test type information to identify production issues.

There is a debate about the effectiveness of administering two vaccine doses versus one, with some evidence showing that a single dose could be adequate in certain situations.
The timing of vaccine doses is crucial, with considerations on how to maximize the number of people vaccinated and the potential risks of delaying the second dose.
Mathematical calculations play a role in determining the efficacy of first doses first strategy, but there are complexities involved, including capacity, prevalence of the virus, and the role of vaccines in reducing spread.

Monitoring trends in Google searches like 'loss of smell' can give insights into Covid-19 outbreaks
Analyzing unusual indicators like reviews of scented candles can provide interesting data on pandemic effects
Utilizing AI and diverse data sources, like mobility data, can help forecast Covid-19 cases more accurately

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Economists and epidemiologists have distinct biases, with the former focused on persuasive economic arguments while the latter often struggles to convince people to act on health advice.
Epidemiologists tend to highlight worst-case scenarios to persuade action, which can sometimes lead to mistrust in projections and slower government responses.
The tools of persuasion differ between economists and epidemiologists, with economists relying on data while epidemiologists are still evolving their policy-making approaches.

Achieving herd immunity through infection can be a challenging policy due to individual behaviors impacting the rate of infection.
To accelerate the spread of Covid-19 for herd immunity, potential strategies include mask prohibitions, creating situations for people to congregate indoors for extended periods, and avoiding widespread testing.
Implementing unconventional and counterintuitive measures like not announcing vaccine progress, encouraging large gatherings such as political rallies, or subsidizing risky activities could be attempts to expedite herd immunity.

The growth rate of daily deaths from COVID-19 falls rapidly within 30 days post reaching 25 cumulative deaths, a pattern observed universally.
After the initial decline, the growth rate of daily deaths hovers around zero or slightly below, suggesting a steady rate of new deaths each day.
Variability in growth rates of deaths among regions decreases after the initial epidemic period, stabilizing around zero, indicating similar experiences across regions.

Testing for a virus like Covid-19 helps solve the information problem for pandemics, potentially saving costs and impacting decisions like diagnosis, clearance, surveillance, and mitigation.
The effectiveness of tests relies on the prevalence of the virus in the population; when prevalence is low, test results can be noisier and less useful.
Contact tracing complements testing by providing additional information, especially in increasing the value of imperfect tests by identifying those more likely to be infected.

People's behavior plays a significant role in determining how a pandemic like Covid-19 progresses, even more than epidemiological models predict.
Understanding the concept of R0, the basic reproduction number, helps in identifying peak infection points and herd immunity thresholds.
Human behavior can cause fluctuations in the effective reproduction rate of a virus, ultimately leading to an equilibrium point where the virus becomes stable and endemic.

During a pandemic, the concept of trade-offs between public health and economy shifts. The pandemic alters the production possibilities set, making it crucial to prioritize health over wealth.
In a pandemic, the production possibilities set shows that there is a significant 'bite' where choosing between preserving public health or the economy becomes an either/or situation.
Implementing widespread and accessible testing for COVID-19 can help reduce the economic impact while maintaining public health, weakening the trade-off between the two.