The disproportionate case-fatality ratio of COVID-19 between countries with the highest vaccination rates and the rest of the world.

Objectives: The global reported cumulative case-fatality ratios (rCFRs) and excess mortality rates of the 20 countries with the highest coronavirus disease 2019 (COVID-19) vaccination rates, the rest of the world and Sub-Saharan Africa (SSA) were compared before and after the commencement of vaccination programmes. Methods: A time series model was used to understand the trend of rCFR over time, and a generalized linear mixed model was used to understand the effect of vaccination on rCFR. Results: By 31 December 2022, an average of 260.3 doses of COVID-19 vaccine per 100 population had been administered in the top 20 vaccinated countries, compared with 152.1 doses in the rest of the world and 51.2 doses in SSA. The mean rCFR of COVID-19 had decreased by 69.0% in the top 20 vaccinated countries, 26.5% in the rest of the world and 7.6% in SSA. Excess mortality had decreased by 48.7% in the top 20 vaccinated countries, compared with 62.5% in the rest of the world and 60.7% in SSA. In a generalized linear mixed model, the reported number of vaccine doses administered (/100 population) (odds ratio 0.64) was associated with a steeper reduction in COVID-19 rCFR. Conclusions: Vaccine equity and faster roll-out across the world is critically important in reducing COVID-19 transmission and CFR.

How prepared is the world? Identifying weaknesses in existing assessment frameworks for global health security through a One Health approach.

The COVID-19 pandemic has exposed faults in the way we assess preparedness and response capacities for public health emergencies. Existing frameworks are limited in scope, and do not sufficiently consider complex social, economic, political, regulatory, and ecological factors. One Health, through its focus on the links among humans, animals, and ecosystems, is a valuable approach through which existing assessment frameworks can be analysed and new ways forward proposed. Although in the past few years advances have been made in assessment tools such as the International Health Regulations Joint External Evaluation, a rapid and radical increase in ambition is required. To sufficiently account for the range of complex systems in which health emergencies occur, assessments should consider how problems are defined across stakeholders and the wider sociopolitical environments in which structures and institutions operate. Current frameworks do little to consider anthropogenic factors in disease emergence or address the full array of health security hazards across the social-ecological system. A complex and interdependent set of challenges threaten human, animal, and ecosystem health, and we cannot afford to overlook important contextual factors, or the determinants of these shared threats. Health security assessment frameworks should therefore ensure that the process undertaken to prioritise and build capacity adheres to core One Health principles and that interventions and outcomes are assessed in terms of added value, trade-offs, and cobenefits across human, animal, and environmental health systems.

Measures, Gaps, and Mitigation Strategies in Bangladesh's COVID-19 Response.

The Coronavirus Disease 2019 (COVID-19) spread rapidly from China to most other countries around the world in early 2020 killing millions of people. To prevent virus spread, world governments implemented a variety of response measures. This paper's objectives were to discuss the country's adopted measures to combat the virus through June 2020, identify gaps in the measures' effectiveness, and offer possible mitigations to those gaps. The measures taken included screening device deployment across international air and land ports, flight suspensions and closures from COVID-19 affected countries, and declaration and extension of a national public holiday (equivalent to lockdowns in other countries). Identified gaps were test kit, PPE, ICU beds, and ventilator shortages, limited public awareness, and insufficient coordination and collaboration among national and international partners. Proper and timely risk mapping, preparedness, communication, coordination, and collaboration among governments and organizations, and public awareness and engagement would have provided sufficient COVID-19 mitigation in Bangladesh.

Zoonotic Tuberculosis - The Changing Landscape.

Despite slow reductions in the annual burden of active human tuberculosis (TB) cases, zoonotic TB (zTB) remains a poorly monitored and an important unaddressed global problem. There is a higher incidence in some regions and countries, especially where close association exists between growing numbers of cattle (the major source of Mycobacterium bovis) and people, many suffering from poverty, and where dairy products are consumed unpasteurised. More attention needs to be focused on possible increased zTB incidence resulting from growth in dairy production globally and increased demand in low income countries in particular. Evidence of new zoonotic mycobacterial strains in South Asia and Africa (e.g. M. orygis), warrants urgent assessment of prevalence, potential drivers and risk in order to develop appropriate interventions. Control of M. bovis infection in cattle through detect and cull policies remain the mainstay of reducing zTB risk, whilst in certain circumstances animal vaccination is proving beneficial. New point of care diagnostics will help to detect animal infections and human cases. Given the high burden of human tuberculosis (caused by M. tuberculosis) in endemic areas, animals are affected by reverse zoonosis, including multi-drug resistant strains. This, may create drug resistant reservoirs of infection in animals. Like COVID-19, zTB is evolving in an ever-changing global landscape.

Zoonotic disease preparedness in sub-Saharan African countries.

BACKGROUND: The emergence of high consequence pathogens such as Ebola and SARS-CoV-2, along with the continued burden of neglected diseases such as rabies, has highlighted the need for preparedness for emerging and endemic infectious diseases of zoonotic origin in sub-Saharan Africa (SSA) using a One Health approach. To identify trends in SSA preparedness, the World Health Organization (WHO) Joint External Evaluation (JEE) reports were analysed. JEEs are voluntary, collaborative processes to assess country's capacities to prevent, detect and rapidly respond to public health risks. This report aimed to analyse the JEE zoonotic disease preparedness data as a whole and identify strengths and weaknesses. METHODS: JEE zoonotic disease preparedness scores for 44 SSA countries who had completed JEEs were analysed. An overall zoonotic disease preparedness score was calculated as an average of the sum of all the SSA country zoonotic disease preparedness scores and compared to the overall mean JEE score. Zoonotic disease preparedness indicators were analysed and data were collated into regions to identify key areas of strength. RESULTS: The mean 'Zoonotic disease' preparedness score (2.35, range 1.00-4.00) was 7% higher compared to the mean overall JEE preparedness score (2.19, range 1.55-3.30), putting 'Zoonotic Diseases' 5th out of 19 JEE sub-areas for preparedness. The average scores for each 'Zoonotic Disease' category were 2.45 for 'Surveillance Systems', 2.76 for 'Veterinary Workforce' and 1.84 for 'Response Mechanisms'. The Southern African region scored highest across the 'Zoonotic disease' categories (2.87).A multisectoral priority zoonotic pathogens list is in place for 43% of SSA countries and 70% reported undertaking national surveillance on 1-5 zoonotic diseases. 70% of SSA countries reported having public health training courses in place for veterinarians and 30% had veterinarians in all districts (reported as sufficient staffing). A multisectoral action plan for zoonotic outbreaks was in place for 14% countries and 32% reported having an established inter-agency response team for zoonotic outbreaks. The zoonotic diseases that appeared most in reported country priority lists were rabies and Highly Pathogenic Avian Influenza (HPAI) (both 89%), anthrax (83%), and brucellosis (78%). CONCLUSIONS: With 'Zoonotic Diseases' ranking 5th in the JEE sub-areas and a mean SSA score 7% greater than the overall mean JEE score, zoonotic disease preparedness appears to have the attention of most SSA countries. However, the considerable range suggests that some countries have more measures in place than others, which may perhaps reflect the geography and types of pathogens that commonly occur. The category 'Response Mechanisms' had the lowest mean score across SSA, suggesting that implementing a multisectoral action plan and response team could provide the greatest gains.

Estimation of novel coronavirus (COVID-19) reproduction number and case fatality rate: A systematic review and meta-analysis.

BACKGROUND AND AIMS: Realizing the transmission potential and the magnitude of the coronavirus disease 2019 (COVID-19) aids public health monitoring, strategies, and preparation. Two fundamental parameters, the basic reproduction number (R 0) and case fatality rate (CFR) of COVID-19, help in this understanding process. The objective of this study was to estimate the R 0 and CFR of COVID-19 and assess whether the parameters vary in different regions of the world. METHODS: We carried out a systematic review to find the reported estimates of the R 0 and the CFR in articles from international databases between January 1 and August 31, 2020. Random-effect models and Forest plots were implemented to evaluate the mean effect size of R 0 and the CFR. Furthermore, R 0 and CFR of the studies were quantified based on geographic location, the tests/thousand population, and the median population age of the countries where the studies were conducted. To assess statistical heterogeneity among the selected articles, the I 2 statistic and the Cochran's Q test were used. RESULTS: Forty-five studies involving R 0 and 34 studies involving CFR were included. The pooled estimation of R 0 was 2.69 (95% CI: 2.40, 2.98), and that of the CFR was 2.67 (2.25, 3.13). The CFR in different regions of the world varied significantly, from 2.49 (2.08, 2.94) in Asia to 3.40 (2.81, 4.04) in North America. We observed higher mean CFR values for the countries with lower tests (3.15 vs 2.16) and greater median population age (3.13 vs 2.27). However, R 0 did not vary significantly in different regions of the world. CONCLUSIONS: An R 0 of 2.69 and a CFR of 2.67 indicate the severity of the COVID-19. Although R 0 and CFR may vary over time, space, and demographics, we recommend considering these figures in control and prevention measures.

The Global Case-Fatality Rate of COVID-19 Has Been Declining Since May 2020.

The objective of this study was to evaluate the trend of reported case fatality rate (rCFR) of COVID-19 over time, using globally reported COVID-19 cases and mortality data. We collected daily COVID-19 diagnoses and mortality data from the WHO's daily situation reports dated January 1 to December 31, 2020. We performed three time-series models [simple exponential smoothing, auto-regressive integrated moving average, and automatic forecasting time-series (Prophet)] to identify the global trend of rCFR for COVID-19. We used beta regression models to investigate the association between the rCFR and potential predictors of each country and reported incidence rate ratios (IRRs) of each variable. The weekly global cumulative COVID-19 rCFR reached a peak at 7.23% during the 17th week (April 22-28, 2020). We found a positive and increasing trend for global daily rCFR values of COVID-19 until the 17th week (pre-peak period) and then a strong declining trend up until the 53rd week (post-peak period) toward 2.2% (December 29-31, 2020). In pre-peak of rCFR, the percentage of people aged 65 and above and the prevalence of obesity were significantly associated with the COVID-19 rCFR. The declining trend of global COVID-19 rCFR was not merely because of increased COVID-19 testing, because COVID-19 tests per 1,000 population had poor predictive value. Decreasing rCFR could be explained by an increased rate of infection in younger people or by the improvement of health care management, shielding from infection, and/or repurposing of several drugs that had shown a beneficial effect on reducing fatality because of COVID-19.

Epidemiology of COVID-19 infection in young children under five years: A systematic review and meta-analysis.

INTRODUCTION: Emerging evidence suggests young children are at greater risk of COVID-19 infection than initially predicted. However, a comprehensive understanding of epidemiology of COVID-19 infection in young children under five years, the most at-risk age-group for respiratory infections, remain unclear. We conducted a systematic review and meta-analysis of epidemiological and clinical characteristics of COVID-19 infection in children under five years. METHOD: Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses , we searched several electronic databases (Pubmed, EMBASE, Web of Science, and Scopus) with no language restriction for published epidemiological studies and case-reports reporting laboratory-confirmed COVID-19 infection in children under five years until June 4, 2020. We assessed pooled prevalence for key demographics and clinical characteristics using Freeman-Tukey double arcsine random-effects model for studies except case-reports. We evaluated risk of bias separately for case-reports and other studies. RESULTS: We identified 1,964 articles, of which, 65 articles were eligible for systematic review that represented 1,214 children younger than five years with laboratory-confirmed COVID-19 infection. The pooled estimates showed that 50% young COVID-19 cases were infants (95% CI: 36% - 63%, 27 studies); 53% were male (95% CI: 41% - 65%, 24 studies); 43% were asymptomatic (95% CI: 15% - 73%, 9 studies) and 7% (95% CI: 0% - 30%, 5 studies) had severe disease that required intensive-care-unit admission. Of 139 newborns from COVID-19 infected mothers, five (3.6%) were COVID-19 positive. There was only one death recorded. DISCUSSION: This systematic review reports the largest number of children younger than five years with COVID-19 infection till date. Our meta-analysis shows nearly half of young COVID-19 cases were asymptomatic and half were infants, highlighting the need for ongoing surveillance to better understand the epidemiology, clinical pattern, and transmission of COVID-19 to develop effective preventive strategies against COVID-19 disease in young paediatric population.

COVID-19-Zoonosis or Emerging Infectious Disease?

The World Health Organization defines a zoonosis as any infection naturally transmissible from vertebrate animals to humans. The pandemic of Coronavirus disease (COVID-19) caused by SARS-CoV-2 has been classified as a zoonotic disease, however, no animal reservoir has yet been found, so this classification is premature. We propose that COVID-19 should instead be classified an "emerging infectious disease (EID) of probable animal origin." To explore if COVID-19 infection fits our proposed re-categorization vs. the contemporary definitions of zoonoses, we reviewed current evidence of infection origin and transmission routes of SARS-CoV-2 virus and described this in the context of known zoonoses, EIDs and "spill-over" events. Although the initial one hundred COVID-19 patients were presumably exposed to the virus at a seafood Market in China, and despite the fact that 33 of 585 swab samples collected from surfaces and cages in the market tested positive for SARS-CoV-2, no virus was isolated directly from animals and no animal reservoir was detected. Elsewhere, SARS-CoV-2 has been detected in animals including domesticated cats, dogs, and ferrets, as well as captive-managed mink, lions, tigers, deer, and mice confirming zooanthroponosis. Other than circumstantial evidence of zoonotic cases in mink farms in the Netherlands, no cases of natural transmission from wild or domesticated animals have been confirmed. More than 40 million human COVID-19 infections reported appear to be exclusively through human-human transmission. SARS-CoV-2 virus and COVID-19 do not meet the WHO definition of zoonoses. We suggest SARS-CoV-2 should be re-classified as an EID of probable animal origin.

Lockdown measures in response to COVID-19 in nine sub-Saharan African countries.

Lockdown measures have been introduced worldwide to contain the transmission of COVID-19. However, the term 'lockdown' is not well-defined. Indeed, WHO's reference to 'so-called lockdown measures' indicates the absence of a clear and universally accepted definition of the term 'lockdown'. We propose a definition of 'lockdown' based on a two-by-two matrix that categorises different communicable disease measures based on whether they are compulsory or voluntary; and whether they are targeted at identifiable individuals or facilities, or whether they are applied indiscriminately to a general population or area. Using this definition, we describe the design, timing and implementation of lockdown measures in nine countries in sub-Saharan Africa: Ghana, Nigeria, South Africa, Sierra Leone, Sudan, Tanzania, Uganda, Zambia and Zimbabwe. While there were some commonalities in the implementation of lockdown across these countries, a more notable finding was the variation in the design, timing and implementation of lockdown measures. We also found that the number of reported cases is heavily dependent on the number of tests carried out, and that testing rates ranged from 2031 to 63 928 per million population up until 7 September 2020. The reported number of COVID-19 deaths per million population also varies (0.4 to 250 up until 7 September 2020), but is generally low when compared with countries in Europe and North America. While lockdown measures may have helped inhibit community transmission, the pattern and nature of the epidemic remains unclear. However, there are signs of lockdown harming health by affecting the functioning of the health system and causing social and economic disruption.

The Global Health Security index and Joint External Evaluation score for health preparedness are not correlated with countries' COVID-19 detection response time and mortality outcome.

Global Health Security Index (GHSI) and Joint External Evaluation (JEE) are two well-known health security and related capability indices. We hypothesised that countries with higher GHSI or JEE scores would have detected their first COVID-19 case earlier, and would experience lower mortality outcome compared to countries with lower scores. We evaluated the effectiveness of GHSI and JEE in predicting countries' COVID-19 detection response times and mortality outcome (deaths/million). We used two different outcomes for the evaluation: (i) detection response time, the duration of time to the first confirmed case detection (from 31st December 2019 to 20th February 2020 when every country's first case was linked to travel from China) and (ii) mortality outcome (deaths/million) until 11th March and 1st July 2020, respectively. We interpreted the detection response time alongside previously published relative risk of the importation of COVID-19 cases from China. We performed multiple linear regression and negative binomial regression analysis to evaluate how these indices predicted the actual outcome. The two indices, GHSI and JEE were strongly correlated (r = 0.82), indicating a good agreement between them. However, both GHSI (r = 0.31) and JEE (r = 0.37) had a poor correlation with countries' COVID-19-related mortality outcome. Higher risk of importation of COVID-19 from China for a given country was negatively correlated with the time taken to detect the first case in that country (adjusted R2 = 0.63-0.66), while the GHSI and JEE had minimal predictive value. In the negative binomial regression model, countries' mortality outcome was strongly predicted by the percentage of the population aged 65 and above (incidence rate ratio (IRR): 1.10 (95% confidence interval (CI): 1.01-1.21) while overall GHSI score (IRR: 1.01 (95% CI: 0.98-1.01)) and JEE (IRR: 0.99 (95% CI: 0.96-1.02)) were not significant predictors. GHSI and JEE had lower predictive value for detection response time and mortality outcome due to COVID-19. We suggest introduction of a population healthiness parameter, to address demographic and comorbidity vulnerabilities, and reappraisal of the ranking system and methods used to obtain the index based on experience gained from this pandemic.

Passengers' destinations from China: low risk of Novel Coronavirus (2019-nCoV) transmission into Africa and South America.

Novel Coronavirus (2019-nCoV [SARS-COV-2]) was detected in humans during the last week of December 2019 at Wuhan city in China, and caused 24 554 cases in 27 countries and territories as of 5 February 2020. The objective of this study was to estimate the risk of transmission of 2019-nCoV through human passenger air flight from four major cities of China (Wuhan, Beijing, Shanghai and Guangzhou) to the passengers' destination countries. We extracted the weekly simulated passengers' end destination data for the period of 1-31 January 2020 from FLIRT, an online air travel dataset that uses information from 800 airlines to show the direct flight and passengers' end destination. We estimated a risk index of 2019-nCoV transmission based on the number of travellers to destination countries, weighted by the number of confirmed cases of the departed city reported by the World Health Organization (WHO). We ranked each country based on the risk index in four quantiles (4th quantile being the highest risk and 1st quantile being the lowest risk). During the period, 388 287 passengers were destined for 1297 airports in 168 countries or territories across the world. The risk index of 2019-nCoV among the countries had a very high correlation with the WHO-reported confirmed cases (0.97). According to our risk score classification, of the countries that reported at least one Coronavirus-infected pneumonia (COVID-19) case as of 5 February 2020, 24 countries were in the 4th quantile of the risk index, two in the 3rd quantile, one in the 2nd quantile and none in the 1st quantile. Outside China, countries with a higher risk of 2019-nCoV transmission are Thailand, Cambodia, Malaysia, Canada and the USA, all of which reported at least one case. In pan-Europe, UK, France, Russia, Germany and Italy; in North America, USA and Canada; in Oceania, Australia had high risk, all of them reported at least one case. In Africa and South America, the risk of transmission is very low with Ethiopia, South Africa, Egypt, Mauritius and Brazil showing a similar risk of transmission compared to the risk of any of the countries where at least one case is detected. The risk of transmission on 31 January 2020 was very high in neighbouring Asian countries, followed by Europe (UK, France, Russia and Germany), Oceania (Australia) and North America (USA and Canada). Increased public health response including early case recognition, isolation of identified case, contract tracing and targeted airport screening, public awareness and vigilance of health workers will help mitigate the force of further spread to naïve countries.