A simple approach to measure transmissibility and forecast incidence

Outbreaks of novel pathogens such as SARS, pandemic influenza and Ebola require substantial investments in reactive interventions, with consequent implementation plans sometimes revised on a weekly basis. Therefore, short-term forecasts of incidence are often of high priority. In light of the recent Ebola epidemic in West Africa, a forecasting exercise was convened by a network of infectious disease modellers. The challenge was to forecast unseen “future” simulated data for four different scenarios at five different time points. In a similar method to that used during the recent Ebola epidemic, we estimated current levels of transmissibility, over variable time-windows chosen in an ad hoc way. Current estimated transmissibility was then used to forecast near-future incidence. We performed well within the challenge and often produced accurate forecasts. A retrospective analysis showed that our subjective method for deciding on the window of time with which to estimate transmissibility often resulted in the optimal choice. However, when near-future trends deviated substantially from exponential patterns, the accuracy of our forecasts was reduced. This exercise highlights the urgent need for infectious disease modellers to develop more robust descriptions of processes – other than the widespread depletion of susceptible individuals – that produce non-exponential patterns of incidence

Comparison of molecular testing strategies for COVID-19 control: a mathematical modelling study

BACKGROUND: WHO has called for increased testing in response to the COVID-19 pandemic, but countries have taken different approaches and the effectiveness of alternative strategies is unknown. We aimed to investigate the potential impact of different testing and isolation strategies on transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: We developed a mathematical model of SARS-CoV-2 transmission based on infectiousness and PCR test sensitivity over time since infection. We estimated the reduction in the effective reproduction number (R) achieved by testing and isolating symptomatic individuals, regular screening of high-risk groups irrespective of symptoms, and quarantine of contacts of laboratory-confirmed cases identified through test-and-trace protocols. The expected effectiveness of different testing strategies was defined as the percentage reduction in R. We reviewed data on the performance of antibody tests reported by the Foundation for Innovative New Diagnostics and examined their implications for the use of so-called immunity passports. FINDINGS: If all individuals with symptoms compatible with COVID-19 self-isolated and self-isolation was 100% effective in reducing onwards transmission, self-isolation of symptomatic individuals would result in a reduction in R of 47% (95% uncertainty interval [UI] 32-55). PCR testing to identify SARS-CoV-2 infection soon after symptom onset could reduce the number of individuals needing to self-isolate, but would also reduce the effectiveness of self-isolation (around 10% would be false negatives). Weekly screening of health-care workers and other high-risk groups irrespective of symptoms by use of PCR testing is estimated to reduce their contribution to SARS-CoV-2 transmission by 23% (95% UI 16-40), on top of reductions achieved by self-isolation following symptoms, assuming results are available at 24 h. The effectiveness of test and trace depends strongly on coverage and the timeliness of contact tracing, potentially reducing R by 26% (95% UI 14-35) on top of reductions achieved by self-isolation following symptoms, if 80% of cases and contacts are identified and there is immediate testing following symptom onset and quarantine of contacts within 24 h. Among currently available antibody tests, performance has been highly variable, with specificity around 90% or lower for rapid diagnostic tests and 95-99% for laboratory-based ELISA and chemiluminescent assays. INTERPRETATION: Molecular testing can play an important role in prevention of SARS-CoV-2 transmission, especially among health-care workers and other high-risk groups, but no single strategy will reduce R below 1 at current levels of population immunity. Immunity passports based on antibody tests or tests for infection face substantial technical, legal, and ethical challenges. FUNDING: UK Medical Research Council

Report 50: Hospitalisation risk for Omicron cases in England

To assess differences in the risk of hospitalisation between the Omicron variant of concern (1) and the Delta variant, we analysed data from all PCR-confirmed SARS-CoV-2 cases in England with last test specimen dates between 1st and 14th December inclusive. Variant was defined using a combination of S-gene Target Failure (SGTF) and genetic data. Case data were linked by National Health service (NHS) number to the National Immunisation Management System (NIMS) database, the NHS Emergency Care (ECDS) and Secondary Use Services (SUS) hospital episode datasets. Hospital attendance was defined as any record of attendance at a hospital by a case in the 14 days following their last positive PCR test, up to and including the day of attendance. A secondary analysis examined the subset of attendances with a length of stay of one or more days. We used stratified conditional Poisson regression to predict hospitalisation status, with demographic strata defined by age, sex, ethnicity, region, specimen date, index of multiple deprivation and in some analyses, vaccination status. Predictor variables were variant (Omicron or Delta), reinfection status and vaccination status. Overall, we find evidence of a reduction in the risk of hospitalisation for Omicron relative to Delta infections, averaging over all cases in the study period. The extent of reduction is sensitive to the inclusion criteria used for cases and hospitalisation, being in the range 20-25% when using any attendance at hospital as the endpoint, and 40-45% when using hospitalisation lasting 1 day or longer or hospitalisations with the ECDS discharge field recorded as “admitted” as the endpoint (Table 1). These reductions must be balanced against the larger risk of infection with Omicron, due to the reduction in protection provided by both vaccination and natural infection. A previous infection reduces the risk of any hospitalisation by approximately 50% (Table 2) and the risk of a hospital stay of 1+ days by 61% (95%CI:55-65%) (before adjustments for under ascertainment of reinfections). High historical infection attack rates and observed reinfection rates with Omicron mean it is necessary to correct hazard ratio estimates to accurately quantify intrinsic differences in severity between Omicron and Delta and to assess the protection afforded by past infection. The resulting adjustments are moderate (typically less than an increase of 0.2 in the hazard ratio for Omicron vs Delta and a reduction of approximately 0.1 in the hazard ratio for reinfections vs primary infections) but significant for evaluating severity overall. Using a hospital stay of 1+ days as the endpoint, the adjusted estimate of the relative risk of reinfections versus primary cases is 0.31, a 69% reduction in hospitalisation risk (Table 2). Stratifying hospitalisation risk by vaccination state reveals a more complex overall picture, albeit consistent with the unstratified analysis. This showed an apparent difference between those who received AstraZenca (AZ) vaccine versus Pfizer or Moderna (PF/MD) for their primary series (doses 1 and 2). Hazard ratios for hospital attendance with Omicron for PF/MD are similar to those seen for Delta in those vaccination categories, while Omicron hazard ratios are generally lower than for Delta for the AZ vaccination categories. Given the limited samples sizes to date, we caution about over-interpreting these trends, but they are compatible with previous findings that while protection afforded against mild infection from AZ was substantially reduced with the emergency of Delta, protection against more severe outcomes was sustained (2,3). We emphasise that these are estimates which condition upon infection; net vaccine effectiveness against hospital attendance may not vary between the vaccines, given that PF/MD maintain higher effectiveness against symptomatic infection with Omicron than AZ (4). Our estimates will assist in refining mathematical models of potential healthcare demand associated with the unfolding European Omicron wave. The hazard ratios provided in Table 3 can be translated into estimates of vaccine effectiveness (VE) against hospitalisation, given estimates of VE against infection (4). In broad terms, our estimates suggest that individuals who have received at least 2 vaccine doses remain substantially protected against hospitalisation, even if protection against infection has been largely lost against the Omicron variant (4,5)