Model-based analysis of an outbreak of bubonic plague in Cairo in 1801

Bubonic plague has caused three deadly pandemics in human history: from the mid-sixth to mid-eighth century, from the mid-fourteenth to the mid-eighteenth century and from the end of the nineteenth until the mid-twentieth century. Between the second and the third pandemics, plague was causing sporadic outbreaks in only a few countries in the Middle East, including Egypt. Little is known about this historical phase of plague, even though it represents the temporal, geographical and phylogenetic transition between the second and third pandemics. Here we analysed in detail an outbreak of plague that took place in Cairo in 1801, and for which epidemiological data are uniquely available thanks to the presence of medical officers accompanying the Napoleonic expedition into Egypt at that time. We propose a new stochastic model describing how bubonic plague outbreaks unfold in both rat and human populations, and perform Bayesian inference under this model using a particle Markov chain Monte Carlo. Rat carcasses were estimated to be infectious for approximately 4 days after death, which is in good agreement with local observations on the survival of infectious rat fleas. The estimated transmission rate between rats implies a basic reproduction number R0 of approximately 3, causing the collapse of the rat population in approximately 100 days. Simultaneously, the force of infection exerted by each infected rat carcass onto the human population increases progressively by more than an order of magnitude. We also considered human-to-human transmission via pneumonic plague or human specific vectors, but found this route to account for only a small fraction of cases and to be significantly below the threshold required to sustain an outbreak

Report 36: Modelling ICU capacity under different epidemiological scenarios of the COVID-19 pandemic in three western European countries

The coronavirus disease 2019 (COVID-19) pandemic has placed enormous strain on healthcare systems, particularly intensive care units (ICUs), with COVID-19 patient care being a key concern of healthcare system planning for winter 2020/21. Ensuring that all patients who require intensive care, irrespective of COVID-19 status, can access it during this time is essential. This study uses an integrated model of hospital capacity planning and epidemiological projections of COVID-19 patients to estimate the spare capacity of key ICU resources under different epidemic scenarios in France, Germany and Italy across the winter period of 2020/21. In particular, we examine the effect of implementing suppression strategies of varying effectiveness, triggered by different numbers of COVID-19 patients in ICU. The use of a ‘dual-demand’ (COVID-19 and non-COVID-19) patient model and the consideration of multiple ICU resources that determine capacity (beds, doctors, nurses and ventilators) and the interdependencies between them, provides a detailed insight into potential capacity constraints this winter. Without sufficient mitigation, we estimate that COVID-19 ICU patient numbers will exceed those seen in the first peak, resulting in substantial capacity deficits, with beds being consistently found to be the most constrained resource across countries. Lockdowns triggered based on ICU capacity could lead to large improvements in spare capacity during the winter season, with pressure being most effectively alleviated when lockdown is triggered early and implemented at a higher level of suppression. In many cases, maximum deficits are reduced to lower levels which can then be managed by expanding supply-side hospital capacity, to ensure that all patients can receive treatment. The success of such interventions also depends on baseline ICU bed numbers and average non-COVID-19 patient occupancy. We find that lockdowns of longer duration reduce the total number of days in deficit, but triggering lockdown earlier when COVID-19 ICU occupancy is lower is more effective in minimising deficits. Our results highlight the dependencies between different metrics, suggesting that absolute benefits of different strategies must be weighed against the feasibility and drawbacks of different amounts of time spent in lockdown

Key epidemiological drivers and impact of interventions in the 2020 SARS-CoV-2 epidemic in England

We fitted a model of SARS-CoV-2 transmission in care homes and the community to regional surveillance data for England. Compared with other approaches, our model provides a synthesis of multiple surveillance data streams into a single coherent modelling framework allowing transmission and severity to be disentangled from features of the surveillance system. Of the control measures implemented, only national lockdown brought the reproduction number (Rteff ) below 1 consistently; if introduced one week earlier it could have reduced deaths in the first wave from an estimated 48,600 to 25,600 (95% credible interval [95%CrI]: 15,900-38,400). The infection fatality ratio decreased from 1.00% (95%CrI: 0.85%-1.21%) to 0.79% (95%CrI: 0.63%-0.99%), suggesting improved clinical care. The infection fatality ratio was higher in the elderly residing in care homes (23.3%, 95%CrI: 14.7%-35.2%) than those residing in the community (7.9%, 95%CrI: 5.9%-10.3%). On 2nd December 2020 England was still far from herd immunity, with regional cumulative infection incidence between 7.6% (95%CrI: 5.4%-10.2%) and 22.3% (95%CrI: 19.4%-25.4%) of the population. Therefore, any vaccination campaign will need to achieve high coverage and a high degree of protection in vaccinated individuals to allow non-pharmaceutical interventions to be lifted without a resurgence of transmission

Report 26: Reduction in mobility and COVID-19 transmission

In response to the COVID-19 pandemic, countries have sought to control transmission of SARS-CoV-2 by restricting population movement through social distancing interventions, reducing the number of contacts. Mobility data represent an important proxy measure of social distancing. Here, we develop a framework to infer the relationship between mobility and the key measure of population-level disease transmission, the reproduction number (R). The framework is applied to 53 countries with sustained SARS-CoV-2 transmission based on two distinct country-specific automated measures of human mobility, Apple and Google mobility data. For both datasets, the relationship between mobility and transmission was consistent within and across countries and explained more than 85% of the variance in the observed variation in transmissibility. We quantified country-specific mobility thresholds defined as the reduction in mobility necessary to expect a decline in new infections (R<1). While social contacts were sufficiently reduced in France, Spain and the United Kingdom to control COVID-19 as of the 10th of May, we find that enhanced control measures are still warranted for the majority of countries. We found encouraging early evidence of some decoupling of transmission and mobility in 10 countries, a key indicator of successful easing of social-distancing restrictions. Easing social-distancing restrictions should be considered very carefully, as small increases in contact rates are likely to risk resurgence even where COVID-19 is apparently under control. Overall, strong population-wide social-distancing measures are effective to control COVID-19; however gradual easing of restrictions must be accompanied by alternative interventions, such as efficient contacttracing, to ensure control

Report 16: Role of testing in COVID-19 control

The World Health Organization has called for increased molecular testing in response to the COVID-19 pandemic, but different countries have taken very different approaches. We used a simple mathematical model to investigate the potential effectiveness of alternative testing strategies for COVID-19 control. Weekly screening of healthcare workers (HCWs) and other at-risk groups using PCR or point-of-care tests for infection irrespective of symptoms is estimated to reduce their contribution to transmission by 25-33%, on top of reductions achieved by self-isolation following symptoms. Widespread PCR testing in the general population is unlikely to limit transmission more than contact-tracing and quarantine based on symptoms alone, but could allow earlier release of contacts from quarantine. Immunity passports based on tests for antibody or infection could support return to work but face significant technical, legal and ethical challenges. Testing is essential for pandemic surveillance but its direct contribution to the prevention of transmission is likely to be limited to patients, HCWs and other high-risk groups

The Immune Cell Composition in Barrett's Metaplastic Tissue Resembles That in Normal Duodenal Tissue

BACKGROUND AND OBJECTIVE: Barrett's esophagus (BE) is characterized by the transition of squamous epithelium into columnar epithelium with intestinal metaplasia. The increased number and types of immune cells in BE have been indicated to be due to a Th2-type inflammatory process. We tested the alternative hypothesis that the abundance of T-cells in BE is caused by a homing mechanism that is found in the duodenum. PATIENTS AND METHODS: Biopsies from BE and duodenal tissue from 30 BE patients and duodenal tissue from 18 controls were characterized by immmunohistochemistry for the presence of T-cells and eosinophils(eos). Ex vivo expanded T-cells were further phenotyped by multicolor analysis using flowcytometry. RESULTS: The high percentage of CD4(+)-T cells (69±3% (mean±SEM/n = 17, by flowcytometry)), measured by flowcytometry and immunohistochemistry, and the presence of non-activated eosinophils found in BE by immunohistochemical staining, were not different from that found in duodenal tissue. Expanded lymphocytes from these tissues had a similar phenotype, characterized by a comparable but low percentage of αE(CD103) positive CD4(+)cells (44±5% in BE, 43±4% in duodenum of BE and 34±7% in duodenum of controls) and a similar percentage of granzyme-B(+)CD8(+) cells(44±5% in BE, 33±6% in duodenum of BE and 36±7% in duodenum of controls). In addition, a similar percentage of α4β7(+) T-lymphocytes (63±5% in BE, 58±5% in duodenum of BE and 62±8% in duodenum of controls) was found. Finally, mRNA expression of the ligand for α4β7, MAdCAM-1, was also similar in BE and duodenal tissue. No evidence for a Th2-response was found as almost no IL-4(+)-T-cells were seen. CONCLUSION: The immune cell composition (lymphocytes and eosinophils) and expression of intestinal adhesion molecule MAdCAM-1 is similar in BE and duodenum. This supports the hypothesis that homing of lymphocytes to BE tissue is mainly caused by intestinal homing signals rather than to an active inflammatory response

Reduction in mobility and COVID-19 transmission

In response to the COVID-19 pandemic, countries have sought to control SARS-CoV-2 transmission by restricting population movement through social distancing interventions, thus reducing the number of contacts. Mobility data represent an important proxy measure of social distancing, and here, we characterise the relationship between transmission and mobility for 52 countries around the world. Transmission significantly decreased with the initial reduction in mobility in 73% of the countries analysed, but we found evidence of decoupling of transmission and mobility following the relaxation of strict control measures for 80% of countries. For the majority of countries, mobility explained a substantial proportion of the variation in transmissibility (median adjusted R-squared: 48%, interquartile range - IQR - across countries [27–77%]). Where a change in the relationship occurred, predictive ability decreased after the relaxation; from a median adjusted R-squared of 74% (IQR across countries [49–91%]) pre-relaxation, to a median adjusted R-squared of 30% (IQR across countries [12–48%]) post-relaxation. In countries with a clear relationship between mobility and transmission both before and after strict control measures were relaxed, mobility was associated with lower transmission rates after control measures were relaxed indicating that the beneficial effects of ongoing social distancing behaviours were substantial

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. RESULTS: School closures, travel restrictions, community-level lockdown, and contact tracing were introduced concurrently around late January but subsequent epidemic trends differed among provinces. Compared with Hubei, the other five most-affected provinces reported a lower crude case fatality ratio and proportion of critical and severe hospitalised cases. From March 2020, as the local transmission of COVID-19 declined, switching the focus of measures to the testing and quarantine of inbound travellers may have helped to sustain the control of the epidemic. CONCLUSIONS: Aggregated indicators of case notifications and severity distributions are essential for monitoring an epidemic. A publicly available database containing these indicators and information regarding control measures is a useful resource for further research and policy planning in response to the COVID-19 epidemic