Citizens from 13 countries share similar preferences for COVID-19 vaccine allocation priorities.

How does the public want a COVID-19 vaccine to be allocated? We conducted a conjoint experiment asking 15,536 adults in 13 countries to evaluate 248,576 profiles of potential vaccine recipients who varied randomly on five attributes. Our sample includes diverse countries from all continents. The results suggest that in addition to giving priority to health workers and to those at high risk, the public favors giving priority to a broad range of key workers and to those with lower income. These preferences are similar across respondents of different education levels, incomes, and political ideologies, as well as across most surveyed countries. The public favored COVID-19 vaccines being allocated solely via government programs but were highly polarized in some developed countries on whether taking a vaccine should be mandatory. There is a consensus among the public on many aspects of COVID-19 vaccination, which needs to be taken into account when developing and communicating rollout strategies.

Pressure on the Health-Care System and Intensive Care Utilization During the COVID-19 Outbreak in the Lombardy Region of Italy: A Retrospective Observational Study in 43,538 Hospitalized Patients.

During the spring of 2020, the coronavirus disease 2019 (COVID-19) epidemic caused an unprecedented demand for intensive-care resources in the Lombardy region of Italy. Using data on 43,538 hospitalized patients admitted between February 21 and July 12, 2020, we evaluated variations in intensive care unit (ICU) admissions and mortality over the course of 3 periods: the early phase of the pandemic (February 21-March 13), the period of highest pressure on the health-care system (March 14-April 25, when numbers of COVID-19 patients exceeded prepandemic ICU bed capacity), and the declining phase (April 26-July 12). Compared with the early phase, patients aged 70 years or more were less often admitted to an ICU during the period of highest pressure on the health-care system (odds ratio (OR) = 0.47, 95% confidence interval (CI): 0.41, 0.54), with longer ICU delays (incidence rate ratio = 1.82, 95% CI: 1.52, 2.18) and lower chances of dying in the ICU (OR = 0.47, 95% CI: 0.34, 0.64). Patients under 56 years of age had more limited changes in the probability of (OR = 0.65, 95% CI: 0.56, 0.76) and delay to (incidence rate ratio = 1.16, 95% CI: 0.95, 1.42) ICU admission and increased mortality (OR = 1.43, 95% CI: 1.00, 2.07). In the declining phase, all quantities decreased for all age groups. These patterns may suggest that limited health-care resources during the peak phase of the epidemic in Lombardy forced a shift in ICU admission criteria to prioritize patients with higher chances of survival.

Modeling the interplay between demography, social contact patterns, and SARS-CoV-2 transmission in the South West Shewa Zone of Oromia Region, Ethiopia.

BACKGROUND: COVID-19 spread may have a dramatic impact in countries with vulnerable economies and limited availability of, and access to, healthcare resources and infrastructures. However, in sub-Saharan Africa, a low prevalence and mortality have been observed so far. METHODS: We collected data on individuals' social contacts in the South West Shewa Zone (SWSZ) of Ethiopia across geographical contexts characterized by heterogeneous population density, work and travel opportunities, and access to primary care. We assessed how socio-demographic factors and observed mixing patterns can influence the COVID-19 disease burden, by simulating SARS-CoV-2 transmission in remote settlements, rural villages, and urban neighborhoods, under school closure mandate. RESULTS: From national surveillance data, we estimated a net reproduction number of 1.62 (95% CI 1.55-1.70). We found that, at the end of an epidemic mitigated by school closure alone, 10-15% of the population residing in the SWSZ would have been symptomatic and 0.3-0.4% of the population would require mechanical ventilation and/or possibly result in a fatal outcome. Higher infection attack rates are expected in more urbanized areas, but the highest incidence of critical disease is expected in remote subsistence farming settlements. School closure contributed to reduce the reproduction number by 49% and the attack rate of infections by 28-34%. CONCLUSIONS: Our results suggest that the relatively low burden of COVID-19 in Ethiopia observed so far may depend on social mixing patterns, underlying demography, and the enacted school closures. Our findings highlight that socio-demographic factors can also determine marked heterogeneities across different geographical contexts within the same region, and they contribute to understand why sub-Saharan Africa is experiencing a relatively lower attack rate of severe cases compared to high-income countries.

Rapid Review of Social Contact Patterns During the COVID-19 Pandemic.

BACKGROUND: Physical distancing measures aim to reduce person-to-person contact, a key driver of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. In response to unprecedented restrictions on human contact during the coronavirus disease 2019 (COVID-19) pandemic, studies measured social contact patterns under the implementation of physical distancing measures. This rapid review synthesizes empirical data on the changing social contact patterns during the COVID-19 pandemic. METHOD: We conducted a systematic review using PubMed, Medline, Embase, and Google Scholar following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We descriptively compared the distribution of contacts observed during the pandemic to pre-COVID data across countries to explore changes in contact patterns during physical distancing measures. RESULTS: We identified 12 studies reporting social contact patterns during the COVID-19 pandemic. Eight studies were conducted in European countries and eleven collected data during the initial mitigation period in the spring of 2020 marked by government-declared lockdowns. Some studies collected additional data after relaxation of initial mitigation. Most study settings reported a mean of between 2 and 5 contacts per person per day, a substantial reduction compared to pre-COVID rates, which ranged from 7 to 26 contacts per day. This reduction was pronounced for contacts outside of the home. Consequently, levels of assortative mixing by age substantially declined. After relaxation of initial mitigation, mean contact rates increased but did not return to pre-COVID levels. Increases in contacts post-relaxation were driven by working-age adults. CONCLUSION: Information on changes in contact patterns during physical distancing measures can guide more realistic representations of contact patterns in mathematical models for SARS-CoV-2 transmission.

Potential short-term outcome of an uncontrolled COVID-19 epidemic in Lombardy, Italy, February to March 2020.

Sustained coronavirus disease (COVID-19) transmission is ongoing in Italy, with 7,375 reported cases and 366 deaths by 8 March 2020. We provide a model-based evaluation of patient records from Lombardy, predicting the impact of an uncontrolled epidemic on the healthcare system. It has the potential to cause more than 250,039 (95% credible interval (CrI): 147,717-459,890) cases within 3 weeks, including 37,194 (95% CrI: 22,250-67,632) patients requiring intensive care. Aggressive containment strategies are required.

Age-specific SARS-CoV-2 infection fatality ratio and associated risk factors, Italy, February to April 2020.

We analysed 5,484 close contacts of coronavirus disease (COVID-19) cases in Italy, all tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Infection fatality ratio was 0.43% (95% confidence interval (CI): 0.21-0.79) for individuals younger than 70 years and 10.5% (95% CI: 8.0-13.6) for older individuals. Risk of death after infection was 62% lower (95% CI: 31-80) in clusters identified after 16 March 2020 and 1.8-fold higher for males (95% CI: 1.03-3.16).

The introduction of 'No jab, No school' policy and the refinement of measles immunisation strategies in high-income countries.

BACKGROUND: In recent years, we witnessed a resurgence of measles even in countries where, according to WHO guidelines, elimination should have already been achieved. In high-income countries, the raise of anti-vaccination movements and parental vaccine hesitancy are posing major challenges for the achievement and maintenance of high coverage during routine programmes. Italy and France approved new regulations, respectively in 2017 and 2018, aimed at raising immunisation rates among children by introducing mandatory vaccination at school entry. METHODS: We simulated the evolution of measles immunity profiles in seven distinct countries for the period 2018-2050 and evaluated the effect of possible adjustments of immunisation strategies adopted in the past on the overall fraction and age distribution of susceptible individuals in different high-income demographic settings. The proposed model accounts for country-specific demographic components, current immunity gaps and immunisation activities in 2018. Vaccination strategies considered include the enhancement of coverage for routine programmes already in place and the introduction of a compulsory vaccination at primary school entry in countries where universal school enrolment is likely achieved. RESULTS: Our model shows that, under current vaccination policies, the susceptible fraction of the population would remain below measles elimination threshold only in Singapore and South Korea. In the UK, Ireland, the USA and Australia either the increase of coverage of routine programmes above 95% or the introduction of a compulsory vaccination at school entry with coverage above 40% are needed to maintain susceptible individuals below 7.5% up to 2050. Although the implementation of mandatory vaccination at school entry would be surely beneficial in Italy, strategies targeting adults would also be required to avoid future outbreaks in this country. CONCLUSIONS: Current vaccination policies are not sufficient to achieve and maintain measles elimination in most countries. Strategies targeting unvaccinated children before they enter primary school can remarkably enhance the fulfilment of WHO targets.

A Systematic Review of Social Contact Surveys to Inform Transmission Models of Close-contact Infections.

BACKGROUND: Researchers increasingly use social contact data to inform models for infectious disease spread with the aim of guiding effective policies about disease prevention and control. In this article, we undertake a systematic review of the study design, statistical analyses, and outcomes of the many social contact surveys that have been published. METHODS: We systematically searched PubMed and Web of Science for articles regarding social contact surveys. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines as closely as possible. RESULTS: In total, we identified 64 social contact surveys, with more than 80% of the surveys conducted in high-income countries. Study settings included general population (58%), schools or universities (37%), and health care/conference/research institutes (5%). The largest number of studies did not focus on a specific age group (38%), whereas others focused on adults (32%) or children (19%). Retrospective (45%) and prospective (41%) designs were used most often with 6% using both for comparison purposes. The definition of a contact varied among surveys, e.g., a nonphysical contact may require conversation, close proximity, or both. We identified age, time schedule (e.g., weekday/weekend), and household size as relevant determinants of contact patterns across a large number of studies. CONCLUSIONS: We found that the overall features of the contact patterns were remarkably robust across several countries, and irrespective of the study details. By considering the most common approach in each aspect of design (e.g., sampling schemes, data collection, definition of contact), we could identify recommendations for future contact data surveys that may be used to facilitate comparison between studies.

Austerity, measles and mandatory vaccination: cross-regional analysis of vaccination in Italy 2000-14.

Background: Italy has experienced a resurgence in measles since 2015. Although much emphasis has been placed on the role of individuals opting out of vaccination, here we test the hypothesis that large budget reductions in public health spending were also a contributing factor. Methods: Multi-variate statistical models were used to assess the relationship between measles, mumps and rubella (MMR) coverage and real public health expenditure per-capita across Italy's 20 regions covering the period 2000-14. Results: Between 2010 and 2014 Italy's public health expenditure fell by over 2%, although varying among regions. Fixed effects models estimate that each 1% reduction in per-capita public health expenditure was associated with a decrease of 0.5 percentage points (95% CI: 0.36-0.65 percentage points) in MMR coverage, after adjusting for time and regional-specific time trends. The consequences can be illustrated by comparing two regions, Lazio, where public health spending fell by 5% and MMR coverage by over 3 percentage points, and Sardinia, a historically deprived region, where public health spending partly rose and MMR rates remained approximately steady. Conclusion: Adoption of austerity policies in the Italian health system was found to be significantly associated with declining vaccination rates for MMR. However, the recent introduction of mandatory vaccination for Italian children may help counteract this trend.

The potential impact of the demographic transition in the Senegal-Gambia region of sub-Saharan Africa on the burden of infectious disease and its potential synergies with control programmes: the case of hepatitis B.

BACKGROUND: Sub-Saharan Africa (SSA) continues to suffer high communicable disease burdens as its demographic transition (DT) proceeds. Although the consequent changes in population structures influence age-specific contact patterns relevant for transmission, the age distribution of immunity, and the disease burden, investigation of the potential of DT to affect infectious disease epidemiology in regions of SSA has hitherto been overlooked. With a substantial disease burden and complex epidemiology, hepatitis B virus (HBV) represents a prime example of an infection whose epidemiology may be significantly influenced by the DT. METHODS: An age-structured mathematical model for HBV in the Senegal and Gambia (SG) region was set within a demographic framework with varying vital rates mirroring the entire course of the DT there over 1850-2100, to investigate the effects of the DT on HBV epidemiology, with and without the combined action of vaccination. The model was run from its reconstructed ancien régime (old order) demo-epidemiologic equilibrium and calibrated against SG 1950 age-distribution estimates and Gambian pre-vaccination HBV age-prevalence data. RESULTS: The model, which reproduced well demographic and HBV age-prevalence data, predicted a complex transition of HBV epidemiology over the course of the DT. This included a prolonged epoch of expansion alongside population growth and rejuvenation until 1990-2000, followed by a dramatic retreat, mainly reflecting projected fertility decline during the twenty-first century. This transitional pattern was mostly explained by the underlying demographically driven changes in horizontal transmission resulting from the changes in the age structure of the population. During 2000-2150 the HBV burden is predicted to decline by more than 70% even in the absence of vaccination. CONCLUSIONS: Demographic change alone may strongly affect HBV disease burden and shape HBV endemicity. The onset of the demographically driven decline in HBV prevalence, aligned with the expansion of HBV vaccination, forms a synergy potentially boosting effectiveness of control. Such a synergy currently appears to be presenting a "window of opportunity" facilitating HBV elimination which it would be important to exploit and which underlines the importance of taking demographic change into account when assessing the potential longer term impact of vaccination and other control measures.

The impact of demographic changes, exogenous boosting and new vaccination policies on varicella and herpes zoster in Italy: a modelling and cost-effectiveness study.

BACKGROUND: The present study aims to evaluate the cost-effectiveness of the newly introduced varicella and herpes zoster (HZ) vaccination programmes in Italy. The appropriateness of the introduction of the varicella vaccine is highly debated because of concerns about the consequences on HZ epidemiology and the expected increase in the number of severe cases in case of suboptimal coverage levels. METHODS: We performed a cost-utility analysis based on a stochastic individual-based model that considers realistic demographic processes and two different underlying mechanisms of exogenous boosting (temporary and progressive immunity). Routine varicella vaccination is given with a two-dose schedule (15 months, 5-6 years). The HZ vaccine is offered to the elderly (65 years), either alone or in combination with an initial catch-up campaign (66-75 years). The main outcome measures are averted cases and deaths, costs per quality-adjusted life years gained, incremental cost-effectiveness ratios, and net monetary benefits associated with the different vaccination policies. RESULTS: Demographic processes have contributed to shaping varicella and HZ epidemiology over the years, decreasing varicella circulation and increasing the incidence of HZ. The recent introduction of varicella vaccination in Italy is expected to produce an enduring reduction in varicella incidence and, indirectly, a further increase of HZ incidence in the first decades, followed by a significant reduction in the long term. However, the concurrent introduction of routine HZ vaccination at 65 years of age is expected to mitigate this increase and, in the longer run, to reduce HZ burden to its minimum. From an economic perspective, all the considered policies are cost-effective, with the exception of varicella vaccination alone when considering a time horizon of 50 years. These results are robust to parameter uncertainties, to the two different hypotheses on the mechanism driving exogenous boosting, and to different demographic projection scenarios. CONCLUSIONS: The recent introduction of a combined varicella and HZ vaccination programme in Italy will produce significant reductions in the burden of both diseases and is found to be a cost-effective policy. This programme will counterbalance the increasing trend of zoster incidence purely due to demographic processes.

The relative importance of frequency of contacts and duration of exposure for the spread of directly transmitted infections.

The recent availability of survey data on social contact patterns has made possible important advances in the understanding of the social determinants of the spread of close-contact infections, and of the importance of long-lasting contacts for effective transmission to occur. Still, little is known about the relationship between two of the most critical identified factors (frequency of contacts and duration of exposure) and how this relationship applies to different types of infections. By integrating data from two independently collected social surveys (Polymod and time use), we propose a model that combines these two transmission determinants into a new epidemiologically relevant measure of contacts: the number of "suitable" contacts, which is the number of contacts that involve a sufficiently long exposure time to allow for transmission. The validity of this new epidemiological measure is tested against Italian serological data for varicella and parvovirus-B19, with uncertainty evaluated using the Bayesian melding technique. The model performs quite well, indicating that the interplay between time of exposure and contacts is critical for varicella transmission, while for B19 it is the duration of exposure that matters for transmission.

Evaluating vaccination strategies for reducing infant respiratory syncytial virus infection in low-income settings.

BACKGROUND: Respiratory syncytial virus (RSV) is a leading cause of lower respiratory tract disease and related hospitalization of young children in least developed countries. Individuals are repeatedly infected, but it is the first exposure, often in early infancy, that results in the vast majority of severe RSV disease. Unfortunately, due to immunological immaturity, infants are a problematic RSV vaccine target. Several trials are ongoing to identify a suitable candidate vaccine and target group, but no immunization program is yet in place. METHODS: In this work, an individual-based model that explicitly accounts for the socio-demographic population structure is developed to investigate RSV transmission patterns in a rural setting of Kenya and to evaluate the potential effectiveness of alternative population targets in reducing RSV infant infection. RESULTS: We find that household transmission is responsible for 39% of infant infections and that school-age children are the main source of infection within the household, causing around 55% of cases. Moreover, assuming a vaccine-induced protection equivalent to that of natural infection, our results show that annual vaccination of students is the only alternative strategy to routine immunization of infants able to trigger a relevant and persistent reduction of infant infection (on average, of 35.6% versus 41.5% in 10 years of vaccination). Interestingly, if vaccination of pregnant women boosts maternal antibody protection in infants by an additional 4 months, RSV infant infection will be reduced by 31.5%. CONCLUSIONS: These preliminary evaluations support the efforts to develop vaccines and related strategies that go beyond targeting vaccines to those at highest risk of severe disease.

Comprehensive profiling of social mixing patterns in resource poor countries: A mixed methods research protocol.

BACKGROUND: Low-and-middle-income countries (LMICs) bear a disproportionate burden of communicable diseases. Social interaction data inform infectious disease models and disease prevention strategies. The variations in demographics and contact patterns across ages, cultures, and locations significantly impact infectious disease dynamics and pathogen transmission. LMICs lack sufficient social interaction data for infectious disease modeling. METHODS: To address this gap, we will collect qualitative and quantitative data from eight study sites (encompassing both rural and urban settings) across Guatemala, India, Pakistan, and Mozambique. We will conduct focus group discussions and cognitive interviews to assess the feasibility and acceptability of our data collection tools at each site. Thematic and rapid analyses will help to identify key themes and categories through coding, guiding the design of quantitative data collection tools (enrollment survey, contact diaries, exit survey, and wearable proximity sensors) and the implementation of study procedures. We will create three age-specific contact matrices (physical, nonphysical, and both) at each study site using data from standardized contact diaries to characterize the patterns of social mixing. Regression analysis will be conducted to identify key drivers of contacts. We will comprehensively profile the frequency, duration, and intensity of infants' interactions with household members using high resolution data from the proximity sensors and calculating infants' proximity score (fraction of time spent by each household member in proximity with the infant, over the total infant contact time) for each household member. DISCUSSION: Our qualitative data yielded insights into the perceptions and acceptability of contact diaries and wearable proximity sensors for collecting social mixing data in LMICs. The quantitative data will allow a more accurate representation of human interactions that lead to the transmission of pathogens through close contact in LMICs. Our findings will provide more appropriate social mixing data for parameterizing mathematical models of LMIC populations. Our study tools could be adapted for other studies.

Genetic screening for the predisposition to venous thromboembolism: a cost-utility analysis of clinical practice in the Italian health care system.

OBJECTIVES: In the Italian health care system, genetic tests for factor V Leiden and factor II are routinely prescribed to assess the predisposition to venous thromboembolism (VTE) of women who request oral contraception. With specific reference to two subpopulations of women already at risk (i.e., familial history or previous event of VTE), the study aimed to assess whether current screening practices in Italy are cost-effective. METHODS: Two decisional models accrued costs and quality-adjusted life-years (QALY) annually from the perspective of the National Health Service. The two models were derived from a decision analysis exercise concerning testing practices and consequent prescribing behavior for oral contraception conducted with 250 Italian gynecologists. Health care costs were compiled on the basis of 10-year hospital discharge records and the activities of a thrombosis center. Whenever possible, input data were based on the Italian context; otherwise, the data were taken from the international literature. RESULTS: Current testing practices on women with a familial history of VTE generate an incremental cost-effectiveness ratio of €72,412/QALY, which is well above the acceptable threshold of cost-effectiveness of €40,000 to €50,000/QALY. In the case of women with a previous event of VTE, the most frequently used testing strategy is cost-ineffective and leads to an overall loss of QALY. CONCLUSIONS: This study represents the first attempt to conduct a cost-utility analysis of genetic screening practices for the predisposition to VTE in the Italian setting. The results indicate that there is an urgent need to better monitor the indications for which tests for factor V Leiden and factor II are prescribed.

A repeated cross-sectional analysis on the economic impact of SARS-CoV-2 pandemic at the hospital level in Italy.

Italy was the first country in Europe to be hit by the Severe Acute Respiratory Syndrome Coronavirus 2. Little research has been conducted to understand the economic impact of providing care for SARS-CoV-2 patients during the pandemic. Our study aims to quantify the incremental healthcare costs for hospitalizations associated to being discharged before or after the first SARS-CoV-2 case was notified in Italy, and to a positive or negative SARS-CoV-2 notified infection. We used data on hospitalizations for 9 different diagnosis related groups at a large Italian Research Hospital with discharge date between 1st January, 2018 and 31st December 2021. The median overall costs for a hospitalization increased from 2410EUR (IQR: 1588-3828) before the start of the pandemic, to 2645EUR (IQR: 1885-4028) and 3834EUR (IQR: 2463-6413) during the pandemic, respectively for patients SARS-CoV-2 negative and positive patients. Interestingly, according to results of a generalized linear model, the highest increases in the average costs sustained for SARS-CoV-2 positive patients with respect to patients discharged before the pandemic was found among those with diagnoses unrelated to COVID-19, i.e. kidney and urinary tract infections with CC (59.71%), intracranial hemorrhage or cerebral infarction (53.33), and pulmonary edema and respiratory failure (47.47%). Our study highlights the economic burden during the COVID-19 pandemic on the hospital system in Italy based on individual patient data. These results contribute to the to the debate around the efficiency of the healthcare services provision during a pandemic.

Personal risk or societal benefit? Investigating adults' support for COVID-19 childhood vaccination.

Parental hesitancy poses a serious threat to the success of the COVID-19 childhood vaccination campaign. We investigate whether adults' opinions on childhood vaccination can be influenced via two survey experiments in Italy (n = 3,633 participants) and the UK (n = 3,314 participants). Respondents were randomly assigned to: a "risk treatment" that highlighted the potential risks of COVID-19 to a child, a "herd immunity treatment" that emphasized the community benefits of pediatric vaccination, or a control message. Participants' probability of supporting COVID-19 childhood vaccination was then assessed on a 0-100 scale. We find that the "risk treatment" reduced the proportion of Italian parents strongly against vaccination by up to 29.6 %, while increasing the proportion of neutral parents by up to 45.0 %. The "herd immunity treatment", instead, was only effective among non-parents, resulting in a lower proportion of individuals against pediatric vaccination and a higher proportion of individuals in favor (both shifted by around 20 %).

Changing social contact patterns among US workers during the COVID-19 pandemic: April 2020 to December 2021.

Non-pharmaceutical interventions minimize social contacts, hence the spread of respiratory pathogens such as influenza and SARS-CoV-2. Globally, there is a paucity of social contact data from the workforce. In this study, we quantified two-day contact patterns among USA employees. Contacts were defined as face-to-face conversations, involving physical touch or proximity to another individual and were collected using electronic self-kept diaries. Data were collected over 4 rounds from 2020 to 2021 during the COVID-19 pandemic. Mean (standard deviation) contacts reported by 1456 participants were 2.5 (2.5), 8.2 (7.1), 9.2 (7.1) and 10.1 (9.5) across round 1 (April-June 2020), 2 (November 2020-January 2021), 3 (June-August 2021), and 4 (November-December 2021), respectively. Between round 1 and 2, we report a 3-fold increase in the mean number of contacts reported per participant with no major increases from round 2-4. We then modeled SARS-CoV-2 transmission at home, work, and community settings. The model revealed reduced relative transmission in all settings in round 1. Subsequently, transmission increased at home and in the community but remained exceptionally low in work settings. To accurately parameterize models of infection transmission and control, we need empirical social contact data that capture human mixing behavior across time.

Prioritizing COVID-19 vaccine allocation in resource poor settings: Towards an Artificial Intelligence-enabled and Geospatial-assisted decision support framework.

OBJECTIVES: To propose a novel framework for COVID-19 vaccine allocation based on three components of Vulnerability, Vaccination, and Values (3Vs). METHODS: A combination of geospatial data analysis and artificial intelligence methods for evaluating vulnerability factors at the local level and allocate vaccines according to a dynamic mechanism for updating vulnerability and vaccine uptake. RESULTS: A novel approach is introduced including (I) Vulnerability data collection (including country-specific data on demographic, socioeconomic, epidemiological, healthcare, and environmental factors), (II) Vaccination prioritization through estimation of a unique Vulnerability Index composed of a range of factors selected and weighed through an Artificial Intelligence (AI-enabled) expert elicitation survey and scientific literature screening, and (III) Values consideration by identification of the most effective GIS-assisted allocation of vaccines at the local level, considering context-specific constraints and objectives. CONCLUSIONS: We showcase the performance of the 3Vs strategy by comparing it to the actual vaccination rollout in Kenya. We show that under the current strategy, socially vulnerable individuals comprise only 45% of all vaccinated people in Kenya while if the 3Vs strategy was implemented, this group would be the first to receive vaccines.

Using mortuary and burial data to place COVID-19 in Lusaka, Zambia within a global context.

Reported COVID-19 cases and associated mortality remain low in many sub-Saharan countries relative to global averages, but true impact is difficult to estimate given limitations around surveillance and mortality registration. In Lusaka, Zambia, burial registration and SARS-CoV-2 prevalence data during 2020 allow estimation of excess mortality and transmission. Relative to pre-pandemic patterns, we estimate age-dependent mortality increases, totalling 3212 excess deaths (95% CrI: 2104-4591), representing an 18.5% (95% CrI: 13.0-25.2%) increase relative to pre-pandemic levels. Using a dynamical model-based inferential framework, we find that these mortality patterns and SARS-CoV-2 prevalence data are in agreement with established COVID-19 severity estimates. Our results support hypotheses that COVID-19 impact in Lusaka during 2020 was consistent with COVID-19 epidemics elsewhere, without requiring exceptional explanations for low reported figures. For more equitable decision-making during future pandemics, barriers to ascertaining attributable mortality in low-income settings must be addressed and factored into discourse around reported impact differences.