In this monthly review of what is new in the world of medical and scientific research, the Medical Forum editorial team has focused on contemporaneous research on COVID-19.

Undocumented cases estimated

A significant number of undocumented cases not being detected or diagnosed due to mild, limited or no symptoms for COVID-19 has been estimated, according to a study published in the journal Science.

The researchers developed a simulated model based on datasets of infections and population movements from 375 Chinese cities before the lockdown in Wuhan on January 23, estimating 86% of all COVID-19 infections in China were undetected prior to the lockdown, while 65% of the cases were detected after the lockdown.

Individuals’ contagiousness has also been estimated with the basic reproductive number (R0) to be 2.38 (95% CI: 2.04−2.77) per COVID-19 infection. Whilst the infection source for 79% of the documented cases was estimated to come from undocumented infections.

Title: Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2) infectious diseases are critical.

DOI: https://doi.org10.1126/science.abb3221

Evidence of early approach

Singapore’s response to COVID-19 has been, so far, effective, considering they were the third country to report cases and had the most reported cases in mid-February, outside of China.

A study published in The Lancet analysed the Singaporean response to three clusters of local transmission cases, found that enhanced pneumonia surveillance, testing of patients in intensive care units and clinicians’ testing, based on clinical or epidemiological suspicion, assisted in early identification of cases. Whilst reactive contact tracing and quarantine of close contacts, ensured no further transmission of the virus.

The researchers emphasised the importance of intensive testing and case-finding among close contacts of diagnosed individuals as crucial to preventing clusters from spreading.

Title: Investigation of three clusters of COVID-19 in Singapore: implications for surveillance and response measures


Suppression vs mitigation

Modelling of non-pharmaceutical interventions has provided an insight into the potential mortality rates and demands on health care services.

A paper published by the Imperial College COVID-19 Response Team analysed two public health strategies: Suppression – reduce the Rto below 1 to eliminate transmission. Mitigation – reduce the Rbut not below 1, to slow the spread of transmission (AKA flatten the curve).

Both strategies were tested with five non-pharmaceutical interventions: case isolation in the home; voluntary home quarantine; social distancing of those over 70 years of age; social distancing of entire population; closure of schools and universities.

Modelling of the most unlikely scenario, no control measures, based on an R0  of 2.4%, predicted 81% of the populations in Great Britain and the United States would be infected, with peak mortality occurring in about three months with 510,000 deaths in Britain and 2.2m in the US. Both countries are predicted in this scenario to reach critical care bed capacity in the second week of April with 30 times the demand greater than resources.

The researchers modelled the ideal mitigation policies (combining home isolation of suspect cases, home quarantine of those living in the same household as suspect cases, and social distancing of the elderly and others at most risk of severe disease) predicting a possible reduction in peak healthcare demand by two thirds and deaths by half.

While modelling of the ideal suppression strategies (combining social distancing of the entire population, home isolation of cases and household quarantine of their family members, and possibly supplemented by school and university closures) would need to be maintained until a vaccine is developed to eliminate transmission.

The authors emphasise that suppression may not succeed long term

Title: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand


COVID-19 Open Research Dataset

Looking for peer-reviewed coronavirus information updated in real-time? Head over to the COVID-19 Open Research Dataset (CORD-19). This free, open-resource database, exclusively focused on coronavirus research, with more than 29,000 scholarly articles, has been launched on the Semantic Scholar platform.

The database is the most extensive collection of scientific literature related to the ongoing pandemic and features natural-language processing algorithms to assist in searching for specific papers.


Vaccine research

The first phase 1 clinical trial of a potential COVID-19 vaccine is underway in Seattle, Washington, with the first of the 45 participants having already received their first of two doses, which will be given 28 days apart. The participants will be followed up over the next 12 months to assess the drug’s safety and efficacy.

The interventional vaccine, mRNA-1273, was developed with genetic code copied from COVID-19 onto the genetic platform mRNA (messenger RNA) by researchers at the National Institute of Allergy and Infectious Diseases and biotechnology company Moderna Inc.

If phase 1 is successful, the drug will need to go through phases 2 and 3 prior to approval, which is estimated to take up to 18 months.

Title: Phase I, Open-Label, Dose-Ranging Study of the Safety and Immunogenicity of 2019-nCoV Vaccine (mRNA-1273) in Healthy Adults


Immune response to non-severe COVID-19

World-first research about the immune response to non-severe COVID-19 is being conducted by researchers from the Peter Doherty Institute for Infection and Immunity in Melbourne. They analysed blood samples taken from one of the first patients diagnosed with COVID-19 in Australia.

The researchers found the immune system responds to non-severe COVID-19 by recruiting the same immune cell populations as it does with influenza, according to a paper published in Nature.

Title: Breadth of concomitant immune responses prior to patient recovery: a case report of non-severe COVID-19


Global assessment of health security

An analysis of 182 countries health security in the event of a COVID-19 outbreak has found half of the countries were operationally capable, according to a study published in The Lancet.

The study used International Health Regulations (IHR) annual report data and developed a 5-level scale to rate the countries:

Level 1: Very little functional capacity is in place to prevent and control the risk or event.
Level 2: Little functional capacity available on an ad-hoc basis with the support of external resources.
Level 3: The country is functionally capable at the national level; however, effectiveness is low at the subnational levels.
Level 4: The country is functionally capable of dealing with various events at the national and subnational levels.
Level 5: The country’s functional capacity is well advanced and sustainable at all levels of health systems.

The authors found 52 (28%) countries had preventative capacities and 60 (33%) had response capacities at levels 1 or 2, whilst 81 (45%) countries had prevent capacities and 78 (43%) had response capacities at levels 4 or 5, suggesting these countries were operationally ready.

Most countries, 138 (76%), scored highly in detection capabilities. Whereas 44 (24%) countries did not have an effective enabling function for public health risks and events. Over half of the countries, 102 (56%), had level 4 or level 5 enabling function capacities in place. 32 (18%) countries had low readiness and 104 (57%) countries were operationally ready for an outbreak of a novel infectious disease, such as CORVID-19.

Title: Health security capacities in the context of COVID-19 outbreak: an analysis of International Health Regulations annual report data from 182 countries


Global influenza mortality

Although the COVID-19 pandemic is dominating the discourse, the devastation from seasonal influenza epidemics should not be forgotten. Global influenza-associated mortality is estimated to be 389 000 with 67% of deaths among people 65 years and older.

Title: Global mortality associated with seasonal influenza epidemics: New burden estimates and predictors from the GLaMOR Project


COVID-19 research resources

A useful tool to track the latest verified COVID-19 statistics has been developed by Johns Hopkins University.