For COVID-19, as for many infectious diseases, the true level of transmission is frequently underestimated because a substantial proportion of people with the infection are undetected either because they are asymptomatic or have only mild symptoms and thus typically fail to present at healthcare facilities. There may also be neglected or under-served segments of the population who are less likely to access healthcare or testing. Under-detection of cases may be exacerbated during an epidemic, when testing capacity may be limited and restricted to people with severe cases and priority risk groups (such as frontline healthcare workers, elderly people and people with comorbidities). Cases may also be misdiagnosed and attributed to other diseases with similar clinical presentation, such as influenza. Differences in mortality between groups of people and countries are important proxy indicators of relative risk of death that guide policy decisions regarding scarce medical resource allocation during the ongoing COVID-19 pandemic. This document is intended to help countries estimate CFR and, if possible, IFR, as appropriately and accurately as possible, while accounting for possible biases in their estimatio

This report presents three scenarios on the impact of COVID-19 in Africa using economic growth forecasts, mortality and efforts to ameliorate impact through social grants. Likely effects are examined on per capita income, poverty and the attainment of selected Sustainable Development Goals targets. Africa’s development trajectory has suffered a severe setback, with extreme poverty rising in all the scenarios. The pandemic threatens Africa in several ways, and the report provides policy recommendations to reduce vulnerability and strengthen resilience

BMJ Global Health2020;5:e002914. doi:10.1136/bmjgh-2020-002914 The evidence produced in mathematical models plays a key role in shaping policy decisions in pandemics. A key question is therefore how well pandemic models relate to their implementation contexts. Drawing on the cases of Ebola and influenza, we map how sociological and anthropological research contributes in the modelling of pandemics to consider lessons for COVID-19. We show how models detach from their implementation contexts through their connections with global narratives of pandemic response, and how sociological and anthropological research can help to locate models differently. This potentiates multiple models of pandemic response attuned to their emerging situations in an iterative and adaptive science. We propose a more open approach to the modelling of pandemics which envisages the model as an intervention of deliberation in situations of evolving uncertainty. This challenges the ‘business-as-usual’ of evidence-based approaches in global health by accentuating all science, within and beyond pandemics, as ‘emergent’ and ‘adaptive’

The Lancet Global Health Published:May 12, 2020DOI:https://doi.org/10.1016/S2214-109X(20)30229-1

ESTUDIO ENE-COVID19: Segunda Ronda del Estudio Nacional de Sero-Epidemiología de la Infección por SARS-CoV-2 en España; Informe preliminar 3 de Junio de 2020 Informe nº 33. Análisis de los casos de COVID-19 notificados a la RENAVE hasta el 10 de mayo en España a 29 de mayo de 2020. Equipo COVID-19. RENAVE. CNE. CNM (ISCIII) Actualización nº 143. Enfermedad por el coronavirus (COVID-19). 21.06.2020 Sistema de Vigilancia de la mortalidad diaria (MoMo), accessed: 23 June, 2020 Instituto Nacional de Estadística: Población por comunidades, edad (grupos quinquenales), Españoles/Extranjeros, Sexo y Año Own calculation

European Centre for Disease Prevention and Control, as of 10-June-20 EuroMOMONetwork, Bulletin, Week 23, 2020 Worldometer

Simulation

This calculator implements a classical infectious disease model — SEIR (Susceptible → Exposed → Infected → Removed), an idealized model of spread still used in frontlines of research e.g.

In einem häufig verwendeten Modellierungskonzept, den so genannten SEIR-Modellen,1-3 wird die Bevölke-rung in verschiedene Gruppen unterteilt, und die Dy-namik der Infektionen und Erkrankungen wird über eine Modellierung der Übergänge zwischen diesen Gruppen nachgebildet. Die Buchstaben SEIR stehen für die empfänglichen (susceptible), latent infizierten (exposed – infiziert, aber noch nicht infektiös), symp-tomatisch infektiösen (infectious) und schließlich ver-storbenen oder genesenen (recovered) Anteile der Be-völkerun

The purpose of this work is to estimate potential COVID-19 case burdens in each African nation considering various social distancing interventions. Given current trends in case burden, the model estimates the potential resource needs that would be needed under different scenarios. The model is for planning purposes and is based on current understanding and the most up-to-date assumptions. Results reported here are not forecasts but scenarios that may unfold given the assumptions about social-distancing and population health. You can download scenarios for North Africa; Middle Africa; West Africa, East Africa and South Afric