Severe acute respiratory syndrome (SARS) mathematical models and disease parameters: a systematic review.

SARS-CoV-1 was the first documented coronavirus to cause an acute epidemic in humans and remains a priority pathogen owing to the risk of re-emergence. Robust estimates of key epidemiological parameters are essential to guide outbreak responses and inform mathematical models. Existing systematic reviews have been limited in scope, warranting a comprehensive and up-to-date review.

Estimating the burden of mpox among MSM in South Africa.

Despite seeing few cases during the 2022-2023 mpox global outbreak, reports in May-July 2024 of 22 cases among men-who-have-sex-with-men (MSM) in South Africa, including three deaths, have raised concerns about under-reported community transmission. We used a Monte Carlo simulation model to estimate the true epidemic size, considering the increased severity of mpox among MSM living with advanced HIV, documented over-representation of people living with HIV among mpox cases and HIV prevalence in South Africa. We estimate that there have been between 220 and 450 cases among MSM LHIV in South Africa, with a total of 290-560 cases among all MSM.

Lassa fever outbreaks, mathematical models, and disease parameters: a systematic review and meta-analysis.

Background: Understanding the epidemiological parameters and transmission dynamics of Lassa fever, a significant public health threat in west Africa caused by the rodent-borne Lassa virus, is crucial for informing evidence-based interventions and outbreak response strategies. Therefore, our study aimed to collate and enhance understanding of the key epidemiological parameters of Lassa fever.

Methods: We conducted a systematic review, searching PubMed and Web of Science for peer-reviewed studies published from database inception up to June 13, 2024, to compile and analyse key epidemiological parameters, mathematical models, and outbreaks of Lassa fever.

Policy impact of the Imperial College COVID-19 Response Team: global perspective and United Kingdom case study.

Background: Mathematical models and advanced analytics play an important role in policy decision making and mobilizing action. The Imperial College Coronavirus Disease 2019 (COVID-19) Response Team (ICCRT) provided continuous, timely and robust epidemiological analyses to inform the policy responses of governments and public health agencies around the world. This study aims to quantify the policy impact of ICCRT outputs, and understand which evidence was considered policy-relevant during the COVID-19 pandemic.

Ebola virus disease mathematical models and epidemiological parameters: a systematic review.

Ebola virus disease poses a recurring risk to human health. We conducted a systematic review (PROSPERO CRD42023393345) of Ebola virus disease transmission models and parameters published from database inception to July 7, 2023, from PubMed and Web of Science. Two people screened each abstract and full text.

Modelling hepatitis C infection acquired from blood transfusions in the UK between 1970 and 1991 for the Infected Blood Inquiry.

The Statistics Expert Group was convened at the request of the Infected Blood Inquiry to provide estimates of the number of infections and deaths from blood-borne infections including hepatitis B virus, human immunodeficiency virus, hepatitis C virus (HCV) and variant Creutzfeldt Jakob disease, as a direct result of contaminated blood and blood products administered in the United Kingdom of Great Britain and Northern Ireland (UK). In the absence of databases of HCV infections and related deaths for all nations of the UK, a statistical model was required to estimate the number of infections and subsequent deaths from HCV acquired from blood transfusions from January 1970 to August 1991. We present this statistical model in detail alongside the results of its application to each of the four nations in the UK.

Correction: Tracking the incidence and risk factors for SARS-CoV-2 infection using historical maternal booking serum samples.

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Inferring community transmission of SARS-CoV-2 in the United Kingdom using the ONS COVID-19 Infection Survey.

Key epidemiological parameters, including the effective reproduction number, , and the instantaneous growth rate, , generated from an ensemble of models, have been informing public health policy throughout the COVID-19 pandemic in the four nations of the United Kingdom of Great Britain and Northern Ireland (UK). However, estimation of these quantities became challenging with the scaling down of surveillance systems as part of the transition from the "emergency" to "endemic" phase of the pandemic. The Office for National Statistics (ONS) COVID-19 Infection Survey (CIS) provided an opportunity to continue estimating these parameters in the absence of other data streams.

Public awareness of and opinions on the use of mathematical transmission modelling to inform public health policy in the United Kingdom.

Mathematical modelling is used to inform public health policy, particularly so during the COVID-19 pandemic. As the public are key stakeholders, understanding the public perceptions of these tools is vital. To complement our previous study on the science-policy interface, novel survey data were collected via an online panel ('representative' sample) and social media ('non-probability' sample).

Marburg virus disease outbreaks, mathematical models, and disease parameters: a systematic review.

The 2023 Marburg virus disease outbreaks in Equatorial Guinea and Tanzania highlighted the importance of better understanding this lethal pathogen. We did a systematic review (PROSPERO CRD42023393345) of peer-reviewed articles reporting historical outbreaks, modelling studies, and epidemiological parameters focused on Marburg virus disease. We searched PubMed and Web of Science from database inception to March 31, 2023.

Alternative epidemic indicators for COVID-19 in three settings with incomplete death registration systems.

Not all COVID-19 deaths are officially reported, and particularly in low-income and humanitarian settings, the magnitude of reporting gaps remains sparsely characterized. Alternative data sources, including burial site worker reports, satellite imagery of cemeteries, and social media-conducted surveys of infection may offer solutions. By merging these data with independently conducted, representative serological studies within a mathematical modeling framework, we aim to better understand the range of underreporting using examples from three major cities: Addis Ababa (Ethiopia), Aden (Yemen), and Khartoum (Sudan) during 2020.

Adapting field-mosquito collection techniques in a perspective of near-infrared spectroscopy implementation.

Background: Near-infrared spectroscopy (NIRS) has the potential to be a useful tool for assessing key entomological parameters of malaria-transmitting mosquitoes, including age, infectious status and species identity. However, before NIRS can be reliably used in the field at scale, methods for killing mosquitoes and conserving samples prior to NIRS scanning need to be further optimized. Historically, mosquitoes used in studies have been killed with chloroform, although this approach is not without health hazards and should not be used in human dwellings.

Milestone house: The story of a hospice for people with HIV/AIDS.

The HIV/AIDS epidemic of the early 1980s has been extensively documented, with all its epidemiological, scientific and medical impacts. Cultural implications for many sectors of society have been profound and long-lasting. Some areas merit reflection for their ingenuity in the face of a crisis and the effect they have had on clinical practice.

Tracking the incidence and risk factors for SARS-CoV-2 infection using historical maternal booking serum samples.

The early transmission dynamics of SARS-CoV-2 in the UK are unknown but their investigation is critical to aid future pandemic planning. We tested over 11,000 anonymised, stored historic antenatal serum samples, given at two north-west London NHS trusts in 2019 and 2020, for total antibody to SARS-CoV-2 receptor binding domain (anti-RBD). Estimated prevalence of seroreactivity increased from 1% prior to mid-February 2020 to 17% in September 2020.

Back to the Future: Quantifying Wing Wear as a Method to Measure Mosquito Age.

Vector biologists have long sought the ability to accurately quantify the age of wild mosquito populations, a metric used to measure vector control efficiency. This has proven difficult due to the difficulties of working in the field and the biological complexities of wild mosquitoes. Ideal age grading techniques must overcome both challenges while also providing epidemiologically relevant age measurements.

Disease transmission and control modelling at the science-policy interface.

The coronavirus disease 2019 (COVID-19) pandemic has disrupted the lives of billions across the world. Mathematical modelling has been a key tool deployed throughout the pandemic to explore the potential public health impact of an unmitigated epidemic. The results of such studies have informed governments' decisions to implement non-pharmaceutical interventions to control the spread of the virus.

Communicating uncertainty in epidemic models.

While mathematical models of disease transmission are widely used to inform public health decision-makers globally, the uncertainty inherent in results are often poorly communicated. We outline some potential sources of uncertainty in epidemic models, present traditional methods used to illustrate uncertainty and discuss alternative presentation formats used by modelling groups throughout the COVID-19 pandemic. Then, by drawing on the experience of our own recent modelling, we seek to contribute to the ongoing discussion of how to improve upon traditional methods used to visualise uncertainty by providing a suggestion of how this can be presented in a clear and simple manner.

Detection of Plasmodium falciparum in laboratory-reared and naturally infected wild mosquitoes using near-infrared spectroscopy.

There is an urgent need for high throughput, affordable methods of detecting pathogens inside insect vectors to facilitate surveillance. Near-infrared spectroscopy (NIRS) has shown promise to detect arbovirus and malaria in the laboratory but has not been evaluated in field conditions. Here we investigate the ability of NIRS to identify Plasmodium falciparum in Anopheles coluzzii mosquitoes.

Modelling intensive care unit capacity under different epidemiological scenarios of the COVID-19 pandemic in three Western European countries.

Background: The coronavirus disease 2019 (COVID-19) pandemic has placed enormous strain on intensive care units (ICUs) in Europe. Ensuring access to care, irrespective of COVID-19 status, in winter 2020-2021 is essential.

Methods: An integrated model of hospital capacity planning and epidemiological projections of COVID-19 patients is used to estimate the demand for and resultant spare capacity of ICU beds, staff and ventilators under different epidemic scenarios in France, Germany and Italy across the 2020-2021 winter period.

The J-IDEA Pandemic Planner: A Framework for Implementing Hospital Provision Interventions During the COVID-19 Pandemic.

Background: Planning for extreme surges in demand for hospital care of patients requiring urgent life-saving treatment for coronavirus disease 2019 (COVID-19), while retaining capacity for other emergency conditions, is one of the most challenging tasks faced by health care providers and policymakers during the pandemic. Health systems must be well-prepared to cope with large and sudden changes in demand by implementing interventions to ensure adequate access to care. We developed the first planning tool for the COVID-19 pandemic to account for how hospital provision interventions (such as cancelling elective surgery, setting up field hospitals, or hiring retired staff) will affect the capacity of hospitals to provide life-saving care.

Database of epidemic trends and control measures during the first wave of COVID-19 in mainland China.

Objectives: In this data collation study, we aimed to provide a comprehensive database describing the epidemic trends and responses during the first wave of coronavirus disease 2019 (COVID-19) throughout the main provinces in China.

Methods: From mid-January to March 2020, we extracted publicly available data regarding the spread and control of COVID-19 from 31 provincial health authorities and major media outlets in mainland China. Based on these data, we conducted descriptive analyses of the epidemic in the six most-affected provinces.

Adapting hospital capacity to meet changing demands during the COVID-19 pandemic.

Background: To calculate hospital surge capacity, achieved via hospital provision interventions implemented for the emergency treatment of coronavirus disease 2019 (COVID-19) and other patients through March to May 2020; to evaluate the conditions for admitting patients for elective surgery under varying admission levels of COVID-19 patients.

Methods: We analysed National Health Service (NHS) datasets and literature reviews to estimate hospital care capacity before the pandemic (pre-pandemic baseline) and to quantify the impact of interventions (cancellation of elective surgery, field hospitals, use of private hospitals, deployment of former medical staff and deployment of newly qualified medical staff) for treatment of adult COVID-19 patients, focusing on general and acute (G&A) and critical care (CC) beds, staff and ventilators.

Results: NHS England would not have had sufficient capacity to treat all COVID-19 and other patients in March and April 2020 without the hospital provision interventions, which alleviated significant shortfalls in CC nurses, CC and G&A beds and CC junior doctors.