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2.
Int J Infect Dis ; 113 Suppl 1: S68-S72, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1574772

ABSTRACT

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.


Subject(s)
COVID-19 , Tuberculosis , Africa , Animals , Cattle , Humans , Policy , SARS-CoV-2 , Tuberculosis/diagnosis , Tuberculosis/epidemiology , Tuberculosis/prevention & control
4.
One Health Outlook ; 3(1): 5, 2021.
Article in English | MEDLINE | ID: covidwho-1388848

ABSTRACT

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.

5.
Health Sci Rep ; 4(2): e274, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-1222623

ABSTRACT

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.

6.
Am J Trop Med Hyg ; 104(6): 2176-2184, 2021 04 21.
Article in English | MEDLINE | ID: covidwho-1197603

ABSTRACT

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.


Subject(s)
COVID-19/epidemiology , COVID-19/mortality , SARS-CoV-2 , COVID-19 Testing , Global Health , Humans , Incidence , Time Factors
8.
Vaccine ; 39(4): 667-677, 2021 01 22.
Article in English | MEDLINE | ID: covidwho-1023764

ABSTRACT

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.


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , Infectious Disease Transmission, Vertical/statistics & numerical data , SARS-CoV-2/pathogenicity , Adult , Asymptomatic Diseases , COVID-19/pathology , COVID-19/virology , Child, Preschool , Epidemiological Monitoring , Female , Humans , Incidence , Infant , Infant, Newborn , Intensive Care Units , Male , Mothers , Publication Bias/statistics & numerical data , Severity of Illness Index
9.
Front Public Health ; 8: 596944, 2020.
Article in English | MEDLINE | ID: covidwho-979060

ABSTRACT

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.


Subject(s)
COVID-19/classification , Communicable Diseases, Emerging , SARS-CoV-2/classification , Zoonoses , Animals , Animals, Wild , China , Communicable Diseases, Emerging/classification , Communicable Diseases, Emerging/transmission , Communicable Diseases, Emerging/virology , Humans , World Health Organization , Zoonoses/classification , Zoonoses/transmission , Zoonoses/virology
10.
BMJ Glob Health ; 5(10)2020 10.
Article in English | MEDLINE | ID: covidwho-841538

ABSTRACT

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.


Subject(s)
Communicable Disease Control , Coronavirus Infections/prevention & control , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Africa South of the Sahara , Betacoronavirus , COVID-19 , COVID-19 Testing , Clinical Laboratory Techniques/statistics & numerical data , Communicable Disease Control/methods , Communicable Disease Control/statistics & numerical data , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Humans , Pneumonia, Viral/diagnosis , Pneumonia, Viral/epidemiology , SARS-CoV-2
11.
Epidemiol Infect ; 148: e210, 2020 09 07.
Article in English | MEDLINE | ID: covidwho-745891

ABSTRACT

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.


Subject(s)
Betacoronavirus , Coronavirus Infections/diagnosis , Global Health , Pneumonia, Viral/diagnosis , Binomial Distribution , COVID-19 , China/epidemiology , Coronavirus Infections/epidemiology , Coronavirus Infections/mortality , Humans , Pandemics , Pneumonia, Viral/epidemiology , Pneumonia, Viral/mortality , SARS-CoV-2
14.
Epidemiol Infect ; 148: e41, 2020 02 26.
Article in English | MEDLINE | ID: covidwho-2270

ABSTRACT

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.


Subject(s)
Air Travel , Coronavirus Infections/transmission , Disease Outbreaks , Pneumonia, Viral/transmission , Risk Assessment , Africa/epidemiology , Airports , Betacoronavirus , COVID-19 , China/epidemiology , Communicable Diseases, Imported , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Humans , Pneumonia, Viral/diagnosis , Pneumonia, Viral/epidemiology , Population Surveillance , SARS-CoV-2 , South America/epidemiology , Travel Medicine
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