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. We estimate that 69 to 100%, 0.8 to 8.0%, and 3.0 to 6.0% of COVID-19 deaths were reported in each setting, respectively. In future epidemics, and in settings where vital registration systems are limited, using multiple alternative data sources could provide critically needed, improved estimates of epidemic impact. However, ultimately, these systems are needed to ensure that, in contrast to COVID-19, the impact of future pandemics or other drivers of mortality is reported and understood worldwide.

Shielding individuals at high risk of COVID-19: A micro-simulation study

Background: One proposed intervention for mitigating COVID-19 epidemics, particularly in low-income and crisis-affected settings, is to physically isolate individuals at high risk of severe disease and death. This intervention, known as ‘shielding', could be implemented in various ways. If shielding is imperfect, any introduction of infections within the shielding group could cause substantial mortality and negate the intervention's benefits. We explored the effectiveness of shielding under various modalities of implementation and considered mitigation measures to reduce possible harms. Methods: : We used an individual-based model to simulate a COVID-19 epidemic in a population where a fraction above a given age are relocated to shielding residences. We set our simulation with the context of an internally displaced persons' camp in Somaliland, for which we had previously collected data on demographics and social mixing patterns. We compared an unmitigated epidemic with a shielding intervention accompanied by various risk-mitigating measures. We explored the impact of parameters such as residence size, reduction in contacts, basic reproduction number, and prior immunity in the population. Results: : Shielded residences are likely to be breached with infection during the outbreak. Nonetheless, shielding can be effective in preventing COVID-19 infections in the shielded population. The effectiveness of shielding is mostly affected by the size of the shielded residence, and by the degree by which contacts with the outside world are reduced. Reductions in contacts between shielded individuals are only effective in larger shielded residences. In epidemics with a lower reproduction number, the effectiveness of shielding could be negative. Conclusions: : Shielding could be an effective method to protect the most at-risk individuals. It should be considered where other measures cannot easily be implemented, but with attention to the epidemiological situation. Shielding should only be implemented through small to medium-sized shielding residences, with appropriate mitigation measures to prevent subsequent spread.

Evaluating COVID-19 decision-making in a humanitarian setting: The case study of Somalia

The global COVID-19 pandemic is unprecedented in its scope and impact. While a great deal of research has been directed towards the response in high-income countries, relatively little is known about the way in which decision-makers in low-income and crisis-affected countries have contended with the epidemic. Through use of an a priori decision framework, we aimed to evaluate the process of policy and operational decision-making in relation to the COVID-19 response in Somalia, a chronically fragile country, focusing particularly on the use of information and the role of transparency. We undertook a desk review, observed a number of key decision-making fora and conducted a series of key informant and focus group discussions with a range of decision-makers including state authority, civil society, humanitarian and development actors. We found that nearly all actors struggled to make sense of the scale of the epidemic and form an appropriate response. Decisions made during the early months had a large impact on the course of the epidemic response. Decision-makers relied heavily on international norms and were constrained by a number of factors within the political environment including resource limitations, political contestation and low population adherence to response measures. Important aspects of the response suffered from a transparency deficit and would have benefitted from more inclusive decision-making. Development of decision support tools appropriate for crisis-affected settings that explicitly deal with individual and environmental decision factors could lead to more effective and timely epidemic response.

Auditing the quality of epidemic decision-making in Somalia: a pilot evaluation.

OBJECTIVE: To assess decision-making quality through piloting an audit tool among decision-makers responding to the COVID-19 epidemic in Somalia. DESIGN AND SETTING: We utilised a mixed-methods programme evaluation design comprising quantitative and qualitative methods. Decision-makers in Somalia piloted the audit tool generating a scorecard for decision-making in epidemic response. They also participated in key informant interviews discussing their experience with the audit process and results. PARTICIPANTS: A total of 18 decision-makers from two humanitarian agencies responding to COVID-19 in Somalia were recruited to pilot the audit tool. OUTCOME MEASURES AND ANALYSIS: We used thematic analysis to assess the feasibility and perceived utility of the audit tool by intended users (decision-makers). We also calculated Fleiss' Kappa to assess inter-rater agreement in the audit scorecard. RESULTS: The audit highlighted areas of improvement in decision-making among both organisations including in the dimensions of accountability and transparency. Despite the audit occurring in a highly complex operating environment, decision-makers found the process to be feasible and of high utility. The flexibility of the audit approach allowed for organisations to adapt the audit to their needs. As a result, organisation reported a high level of acceptance of the findings. CONCLUSION: Strengthening decision-making processes is key to realising the objectives of epidemic response. This pilot evaluation contributes towards this goal by the testing what, to our knowledge, may be the first tool designed specifically to assess quality of decision-making processes in epidemic response. The tool has proven feasible and acceptable in assessing decision-making quality in an ongoing response and has potential applicability in assessing decision-making in broader humanitarian response.

Adult mortality before and during the first wave of COVID-19 pandemic in nine communities of Yemen: a key informant study.

INTRODUCTION: Widespread armed conflict has affected Yemen since 2014. To date, the mortality toll of seven years of crisis, and any excess due to the COVID-19 pandemic, are not well quantified. We attempted to estimate population mortality during the pre-pandemic and pandemic periods in nine purposively selected urban and rural communities of southern and central Yemen (Aden and Ta'iz governorates), totalling > 100,000 people. METHODS: Within each study site, we collected lists of decedents between January 2014-March 2021 by interviewing different categories of key community informants, including community leaders, imams, healthcare workers, senior citizens and others. After linking records across lists based on key variables, we applied two-, three- or four-list capture-recapture analysis to estimate total death tolls. We also computed death rates by combining these estimates with population denominators, themselves subject to estimation. RESULTS: After interviewing 138 disproportionately (74.6%) male informants, we identified 2445 unique decedents. While informants recalled deaths throughout the study period, reported deaths among children were sparse: we thus restricted analysis to persons aged ≥ 15 years old. We noted a peak in reported deaths during May-July 2020, plausibly coinciding with the first COVID-19 wave. Death rate estimates featured uninformatively large confidence intervals, but appeared elevated compared to the non-crisis baseline, particularly in two sites where a large proportion of deaths were attributed to war injuries. There was no clear-cut evidence of excess mortality during the pandemic period. CONCLUSIONS: We found some evidence of a peak in mortality during the early phase of the pandemic, but death rate estimates were otherwise too imprecise to enable strong inference on trends. Estimates suggested substantial mortality elevations from baseline during the crisis period, but are subject to serious potential biases. The study highlighted challenges of data collection in this insecure, politically contested environment.

Evaluating COVID-19 decision-making in a humanitarian setting: The case study of Somalia.

The global COVID-19 pandemic is unprecedented in its scope and impact. While a great deal of research has been directed towards the response in high-income countries, relatively little is known about the way in which decision-makers in low-income and crisis-affected countries have contended with the epidemic. Through use of an a priori decision framework, we aimed to evaluate the process of policy and operational decision-making in relation to the COVID-19 response in Somalia, a chronically fragile country, focusing particularly on the use of information and the role of transparency. We undertook a desk review, observed a number of key decision-making fora and conducted a series of key informant and focus group discussions with a range of decision-makers including state authority, civil society, humanitarian and development actors. We found that nearly all actors struggled to make sense of the scale of the epidemic and form an appropriate response. Decisions made during the early months had a large impact on the course of the epidemic response. Decision-makers relied heavily on international norms and were constrained by a number of factors within the political environment including resource limitations, political contestation and low population adherence to response measures. Important aspects of the response suffered from a transparency deficit and would have benefitted from more inclusive decision-making. Development of decision support tools appropriate for crisis-affected settings that explicitly deal with individual and environmental decision factors could lead to more effective and timely epidemic response.

The utilisation of vaccines in humanitarian crises, 2015-2019: A review of practice.

BACKGROUND: The risk factors that emerge with the onset and protraction of humanitarian crises leave populations at a heightened risk of excess morbidity and mortality from vaccine-preventable diseases (VPDs). There is currently little clarity on which vaccines are being used in crises throughout the world, and whether vaccination decisions correspond to local disease threats. This review aimed to collect and analyse such information. METHODS: We reviewed vaccination services from January 2015 to June 2019 across all 25 humanitarian responses that had an activated coordination mechanism during this period. A range of online sources and informants within the humanitarian sector were consulted to compile data on which vaccines were provided in each crisis, and the modality and timing of vaccine provision. The package of vaccination services since the start of each crisis was then compared with local disease burden (baseline + excess due to crisis-emergent risk factors). RESULTS: The range of vaccines used in humanitarian crises appears limited. When offered, vaccines were primarily delivered through the pre-existing routine schedule, with few supplementary actions taken in recognition of the need for rapidly enhancing population immunity. Vaccine packages mostly did not address the actual range of VPDs that likely accounted for substantial disease risk. CONCLUSIONS: This review suggests inconsistencies and inequities in vaccine provision to crisis-affected populations. A consistent, standardised and broader approach to vaccine use in crises is needed.

Date of introduction and epidemiologic patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Mogadishu, Somalia: estimates from transmission modelling of satellite-based excess mortality data in 2020.

Background: In countries with weak surveillance systems, confirmed coronavirus disease 2019 (COVID-19) deaths are likely to underestimate the pandemic's death toll. Many countries also have incomplete vital registration systems, hampering excess mortality estimation. Here, we fitted a dynamic transmission model to satellite imagery data of cemeteries in Mogadishu, Somalia during 2020 to estimate the date of introduction and other epidemiologic parameters of the early spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in this low-income, crisis-affected setting. Methods: We performed Markov chain Monte Carlo (MCMC) fitting with an age-structured compartmental COVID-19 model to provide median estimates and credible intervals for the date of introduction, the basic reproduction number ( R 0 ) and the effect of non-pharmaceutical interventions (NPIs) up to August 2020. Results: Under the assumption that excess deaths in Mogadishu March-August 2020 were attributable to SARS-CoV-2 infections, we arrived at median estimates of November-December 2019 for the date of introduction and low R 0 estimates (1.4-1.7) reflecting the slow and early rise and long plateau of excess deaths. The date of introduction, the amount of external seeding, the infection fatality rate (IFR) and the effectiveness of NPIs are correlated parameters and not separately identifiable in a narrow range from deaths data. Nevertheless, to obtain introduction dates no earlier than November 2019 a higher population-wide IFR (≥0.7%) had to be assumed than obtained by applying age-specific IFRs from high-income countries to Somalia's age structure. Conclusions: Model fitting of excess mortality data across a range of plausible values of the IFR and the amount of external seeding suggests an early SARS-CoV-2 introduction event may have occurred in Somalia in November-December 2019. Transmissibility in the first epidemic wave was estimated to be lower than in European settings. Alternatively, there was another, unidentified source of sustained excess mortality in Mogadishu from March to August 2020.

Inference is bliss: Simulation for power estimation for an observational study of a cholera outbreak intervention.

BACKGROUND: The evaluation of ring vaccination and other outbreak-containment interventions during severe and rapidly-evolving epidemics presents a challenge for the choice of a feasible study design, and subsequently, for the estimation of statistical power. To support a future evaluation of a case-area targeted intervention against cholera, we have proposed a prospective observational study design to estimate the association between the strength of implementation of this intervention across several small outbreaks (occurring within geographically delineated clusters around primary and secondary cases named 'rings') and its effectiveness (defined as a reduction in cholera incidence). We describe here a strategy combining mathematical modelling and simulation to estimate power for a prospective observational study. METHODOLOGY AND PRINCIPAL FINDINGS: The strategy combines stochastic modelling of transmission and the direct and indirect effects of the intervention in a set of rings, with a simulation of the study analysis on the model results. We found that targeting 80 to 100 rings was required to achieve power ≥80%, using a basic reproduction number of 2.0 and a dispersion coefficient of 1.0-1.5. CONCLUSIONS: This power estimation strategy is feasible to implement for observational study designs which aim to evaluate outbreak containment for other pathogens in geographically or socially defined rings.

Date of introduction and epidemiologic patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Mogadishu, Somalia: estimates from transmission modelling of satellite-based excess mortality data in 2020 [version 2;peer review: 2 approved]

Background: In countries with weak surveillance systems, confirmed coronavirus disease 2019 (COVID-19) deaths are likely to underestimate the pandemic’s death toll. Many countries also have incomplete vital registration systems, hampering excess mortality estimation. Here, we fitted a dynamic transmission model to satellite imagery data of cemeteries in Mogadishu, Somalia during 2020 to estimate the date of introduction and other epidemiologic parameters of the early spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in this low-income, crisis-affected setting. Methods: We performed Markov chain Monte Carlo (MCMC) fitting with an age-structured compartmental COVID-19 model to provide median estimates and credible intervals for the date of introduction, the basic reproduction number ( R 0) and the effect of non-pharmaceutical interventions (NPIs) up to August 2020. Results: Under the assumption that excess deaths in Mogadishu March-August 2020 were attributable to SARS-CoV-2 infections, we arrived at median estimates of November-December 2019 for the date of introduction and low R 0 estimates (1.4-1.7) reflecting the slow and early rise and long plateau of excess deaths. The date of introduction, the amount of external seeding, the infection fatality rate (IFR) and the effectiveness of NPIs are correlated parameters and not separately identifiable in a narrow range from deaths data. Nevertheless, to obtain introduction dates no earlier than November 2019 a higher population-wide IFR (≥0.7%) had to be assumed than obtained by applying age-specific IFRs from high-income countries to Somalia’s age structure. Conclusions: Model fitting of excess mortality data across a range of plausible values of the IFR and the amount of external seeding suggests an early SARS-CoV-2 introduction event may have occurred in Somalia in November-December 2019. Transmissibility in the first epidemic wave was estimated to be lower than in European settings. Alternatively, there was another, unidentified source of sustained excess mortality in Mogadishu from March to August 2020.

Public and health professional epidemic risk perceptions in countries that are highly vulnerable to epidemics: a systematic review.

BACKGROUND: Risk communication interventions during epidemics aim to modify risk perceptions to achieve rapid shifts in population health behaviours. Exposure to frequent and often concurrent epidemics may influence how the public and health professionals perceive and respond to epidemic risks. This review aimed to systematically examine the evidence on risk perceptions of epidemic-prone diseases in countries highly vulnerable to epidemics. METHODS: We conducted a systematic review using PRISMA standards. We included peer-reviewed studies describing or measuring risk perceptions of epidemic-prone diseases among the general adult population or health professionals in 62 countries considered highly vulnerable to epidemics. We searched seven bibliographic databases and applied a four-stage screening and selection process, followed by quality appraisal. We conducted a narrative meta-synthesis and descriptive summary of the evidence, guided by the Social Amplification of Risk Framework. RESULTS: Fifty-six studies were eligible for the final review. They were conducted in eighteen countries and addressed thirteen epidemic-prone diseases. Forty-five studies were quantitative, six qualitative and five used mixed methods. Forty-one studies described epidemic risk perceptions in the general public and nineteen among health professionals. Perceived severity of epidemic-prone diseases appeared high across public and health professional populations. However, perceived likelihood of acquiring disease varied from low to moderate to high among the general public, and appeared consistently high amongst health professionals. Other occupational groups with high exposure to specific diseases, such as bushmeat handlers, reported even lower perceived likelihood than the general population. Among health professionals, the safety and effectiveness of the work environment and of the broader health system response influenced perceptions. Among the general population, disease severity, familiarity and controllability of diseases were influential factors. However, the evidence on how epidemic risk perceptions are formed or modified in these populations is limited. CONCLUSIONS: The evidence affords some insights into patterns of epidemic risk perception and influencing factors, but inadequately explores what underlies perceptions and their variability, particularly among diseases, populations and over time. Approaches to defining and measuring epidemic risk perceptions are relatively underdeveloped.

Country differences in transmissibility, age distribution and case-fatality of SARS-CoV-2: a global ecological analysis.

Objectives The first COVID-19 pandemic waves in many low-income countries appeared milder than initially forecasted. We conducted a country-level ecological study to describe patterns in key SARS-CoV-2 outcomes by country and region and explore associations with potential explanatory factors, including population age structure and prior exposure to endemic parasitic infections. Methods We collected publicly available data and compared them using standardisation techniques. We then explored the association between exposures and outcomes using random forest and linear regression. We adjusted for potential confounders and plausible effect modifications. Results While mean time-varying reproduction number was highest in the European and Americas regions, median age of death was lower in the Africa region, with a broadly similar case-fatality ratio. Population age was strongly associated with mean (ß=0.01, 95% CI, 0.005, 0.011) and median age of cases (ß=-0.40, 95% CI, -0.53, -0.26) and deaths (ß= 0.40, 95% CI, 0.17, 0.62). Conclusions Population age seems an important country-level factor explaining both transmissibility and age distribution of observed cases and deaths. Endemic infections seem unlikely, from this analysis, to be key drivers of the variation in observed epidemic trends. Our study was limited by the availability of outcome data and its causally uncertain ecological design.

Excess mortality during the COVID-19 pandemic: a geospatial and statistical analysis in Mogadishu, Somalia.

BACKGROUND: While the impact of the COVID-19 pandemic has been well documented in high-income countries, less is known about the health effects in Somalia, where health systems are weak and vital registration is underdeveloped. METHODS: We used remote sensing and geospatial analysis to quantify burial numbers from January 2017 to September 2020 in Mogadishu. We imputed missing grave counts using surface area data. Simple interpolation and a generalised additive mixed growth model were used to predict actual and counterfactual burial rates by cemetery and across Mogadishu during the most likely period of COVID-19 excess mortality and to compute excess burials. We undertook a qualitative survey of key informants to determine the drivers of COVID-19 excess mortality. RESULTS: Burial rates increased during the pandemic, averaging 1.5-fold and peaking at a 2.2-fold increase on pre-pandemic levels. When scaled to plausible range of baseline crude death rates, the excess death toll between January and September 2020 was 3200-11 800. Compared with Barakaat Cemetery Committee's burial records, our estimates were lower. CONCLUSIONS: Our study indicates considerable underestimation of the health effects of COVID-19 in Banadir and an overburdened public health system struggling to deal with the increasing severity of the epidemic in 2020.

Leveraging community mortality indicators to infer COVID-19 mortality and transmission dynamics in Damascus, Syria.

The COVID-19 pandemic has resulted in substantial mortality worldwide. However, to date, countries in the Middle East and Africa have reported considerably lower mortality rates than in Europe and the Americas. Motivated by reports of an overwhelmed health system, we estimate the likely under-ascertainment of COVID-19 mortality in Damascus, Syria. Using all-cause mortality data, we fit a mathematical model of COVID-19 transmission to reported mortality, estimating that 1.25% of COVID-19 deaths (sensitivity range 1.00% - 3.00%) have been reported as of 2 September 2020. By 2 September, we estimate that 4,380 (95% CI: 3,250 - 5,550) COVID-19 deaths in Damascus may have been missed, with 39.0% (95% CI: 32.5% - 45.0%) of the population in Damascus estimated to have been infected. Accounting for under-ascertainment corroborates reports of exceeded hospital bed capacity and is validated by community-uploaded obituary notifications, which confirm extensive unreported mortality in Damascus.

Excess mortality during the COVID-19 pandemic: a geospatial and statistical analysis in Aden governorate, Yemen.

BACKGROUND: The burden of COVID-19 in low-income and conflict-affected countries remains unclear, largely reflecting low testing rates. In parts of Yemen, reports indicated a peak in hospital admissions and burials during May-June 2020. To estimate excess mortality during the epidemic period, we quantified activity across all identifiable cemeteries within Aden governorate (population approximately 1 million) by analysing very high-resolution satellite imagery and compared estimates to Civil Registry office records. METHODS: After identifying active cemeteries through remote and ground information, we applied geospatial analysis techniques to manually identify new grave plots and measure changes in burial surface area over a period from July 2016 to September 2020. After imputing missing grave counts using surface area data, we used alternative approaches, including simple interpolation and a generalised additive mixed growth model, to predict both actual and counterfactual (no epidemic) burial rates by cemetery and across the governorate during the most likely period of COVID-19 excess mortality (from 1 April 2020) and thereby compute excess burials. We also analysed death notifications to the Civil Registry office over the same period. RESULTS: We collected 78 observations from 11 cemeteries. In all but one, a peak in daily burial rates was evident from April to July 2020. Interpolation and mixed model methods estimated ≈1500 excess burials up to 6 July, and 2120 up to 19 September, corresponding to a peak weekly increase of 230% from the counterfactual. Satellite imagery estimates were generally lower than Civil Registry data, which indicated a peak 1823 deaths in May alone. However, both sources suggested the epidemic had waned by September 2020. DISCUSSION: To our knowledge, this is the first instance of satellite imagery being used for population mortality estimation. Findings suggest a substantial, under-ascertained impact of COVID-19 in this urban Yemeni governorate and are broadly in line with previous mathematical modelling predictions, though our method cannot distinguish direct from indirect virus deaths. Satellite imagery burial analysis appears a promising novel approach for monitoring epidemics and other crisis impacts, particularly where ground data are difficult to collect.

Considerations for planning COVID-19 treatment services in humanitarian responses.

The COVID-19 pandemic has the potential to cause high morbidity and mortality in crisis-affected populations. Delivering COVID-19 treatment services in crisis settings will likely entail complex trade-offs between offering services of clinical benefit and minimising risks of nosocomial infection, while allocating resources appropriately and safeguarding other essential services. This paper outlines considerations for humanitarian actors planning COVID-19 treatment services where vaccination is not yet widely available. We suggest key decision-making considerations: allocation of resources to COVID-19 treatment services and the design of clinical services should be based on community preferences, likely opportunity costs, and a clearly articulated package of care across different health system levels. Moreover, appropriate service planning requires information on the expected COVID-19 burden and the resilience of the health system. We explore COVID-19 treatment service options at the patient level (diagnosis, management, location and level of treatment) and measures to reduce nosocomial transmission (cohorting patients, protecting healthcare workers). Lastly, we propose key indicators for monitoring COVID-19 health services.

The practice of evaluating epidemic response in humanitarian and low-income settings: a systematic review.

BACKGROUND: Epidemics of infectious disease occur frequently in low-income and humanitarian settings and pose a serious threat to populations. However, relatively little is known about responses to these epidemics. Robust evaluations can generate evidence on response efforts and inform future improvements. This systematic review aimed to (i) identify epidemics reported in low-income and crisis settings, (ii) determine the frequency with which evaluations of responses to these epidemics were conducted, (iii) describe the main typologies of evaluations undertaken and (iv) identify key gaps and strengths of recent evaluation practice. METHODS: Reported epidemics were extracted from the following sources: World Health Organization Disease Outbreak News (WHO DON), UNICEF Cholera platform, Reliefweb, PROMED and Global Incidence Map. A systematic review for evaluation reports was conducted using the MEDLINE, EMBASE, Global Health, Web of Science, WPRIM, Reliefweb, PDQ Evidence and CINAHL Plus databases, complemented by grey literature searches using Google and Google Scholar. Evaluation records were quality-scored and linked to epidemics based on time and place. The time period for the review was 2010-2019. RESULTS: A total of 429 epidemics were identified, primarily in sub-Saharan Africa, the Middle East and Central Asia. A total of 15,424 potential evaluations records were screened, 699 assessed for eligibility and 132 included for narrative synthesis. Only one tenth of epidemics had a corresponding response evaluation. Overall, there was wide variability in the quality, content as well as in the disease coverage of evaluation reports. CONCLUSION: The current state of evaluations of responses to these epidemics reveals large gaps in coverage and quality and bears important implications for health equity and accountability to affected populations. The limited availability of epidemic response evaluations prevents improvements to future public health response. The diversity of emphasis and methods of available evaluations limits comparison across responses and time. In order to improve future response and save lives, there is a pressing need to develop a standardized and practical approach as well as governance arrangements to ensure the systematic conduct of epidemic response evaluations in low-income and crisis settings.

Response strategies for COVID-19 epidemics in African settings: a mathematical modelling study.

BACKGROUND: The health impact of COVID-19 may differ in African settings as compared to countries in Europe or China due to demographic, epidemiological, environmental and socio-economic factors. We evaluated strategies to reduce SARS-CoV-2 burden in African countries, so as to support decisions that balance minimising mortality, protecting health services and safeguarding livelihoods. METHODS: We used a Susceptible-Exposed-Infectious-Recovered mathematical model, stratified by age, to predict the evolution of COVID-19 epidemics in three countries representing a range of age distributions in Africa (from oldest to youngest average age: Mauritius, Nigeria and Niger), under various effectiveness assumptions for combinations of different non-pharmaceutical interventions: self-isolation of symptomatic people, physical distancing and 'shielding' (physical isolation) of the high-risk population. We adapted model parameters to better represent uncertainty about what might be expected in African populations, in particular by shifting the distribution of severity risk towards younger ages and increasing the case-fatality ratio. We also present sensitivity analyses for key model parameters subject to uncertainty. RESULTS: We predicted median symptomatic attack rates over the first 12 months of 23% (Niger) to 42% (Mauritius), peaking at 2-4 months, if epidemics were unmitigated. Self-isolation while symptomatic had a maximum impact of about 30% on reducing severe cases, while the impact of physical distancing varied widely depending on percent contact reduction and R0. The effect of shielding high-risk people, e.g. by rehousing them in physical isolation, was sensitive mainly to residual contact with low-risk people, and to a lesser extent to contact among shielded individuals. Mitigation strategies incorporating self-isolation of symptomatic individuals, moderate physical distancing and high uptake of shielding reduced predicted peak bed demand and mortality by around 50%. Lockdowns delayed epidemics by about 3 months. Estimates were sensitive to differences in age-specific social mixing patterns, as published in the literature, and assumptions on transmissibility, infectiousness of asymptomatic cases and risk of severe disease or death by age. CONCLUSIONS: In African settings, as elsewhere, current evidence suggests large COVID-19 epidemics are expected. However, African countries have fewer means to suppress transmission and manage cases. We found that self-isolation of symptomatic persons and general physical distancing are unlikely to avert very large epidemics, unless distancing takes the form of stringent lockdown measures. However, both interventions help to mitigate the epidemic. Shielding of high-risk individuals can reduce health service demand and, even more markedly, mortality if it features high uptake and low contact of shielded and unshielded people, with no increase in contact among shielded people. Strategies combining self-isolation, moderate physical distancing and shielding could achieve substantial reductions in mortality in African countries. Temporary lockdowns, where socioeconomically acceptable, can help gain crucial time for planning and expanding health service capacity.

COVID-19 control in low-income settings and displaced populations: what can realistically be done?

COVID-19 prevention strategies in resource limited settings, modelled on the earlier response in high income countries, have thus far focused on draconian containment strategies, which impose movement restrictions on a wide scale. These restrictions are unlikely to prevent cases from surging well beyond existing hospitalisation capacity; not withstanding their likely severe social and economic costs in the long term. We suggest that in low-income countries, time limited movement restrictions should be considered primarily as an opportunity to develop sustainable and resource appropriate mitigation strategies. These mitigation strategies, if focused on reducing COVID-19 transmission through a triad of prevention activities, have the potential to mitigate bed demand and mortality by a considerable extent. This triade is based on a combination of high-uptake of community led shielding of high-risk individuals, self-isolation of mild to moderately symptomatic cases, and moderate physical distancing in the community. We outline a set of principles for communities to consider how to support the protection of the most vulnerable, by shielding them from infection within and outside their homes. We further suggest three potential shielding options, with their likely applicability to different settings, for communities to consider and that would enable them to provide access to transmission-shielded arrangements for the highest risk community members. Importantly, any shielding strategy would need to be predicated on sound, locally informed behavioural science and monitored for effectiveness and evaluating its potential under realistic modelling assumptions. Perhaps, most importantly, it is essential that these strategies not be perceived as oppressive measures and be community led in their design and implementation. This is in order that they can be sustained for an extended period of time, until COVID-19 can be controlled or vaccine and treatment options become available.