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1.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-329751

ABSTRACT

Background Post COVID-19 Condition (PCC) as defined by WHO refers to a wide range of new, returning, or ongoing health problems experienced by COVID-19 survivors, and represents a rapidly emerging public health priority. We aimed to establish how this developing condition has impacted patients in South Africa and which population groups are at risk. Methods In this prospective cohort study, participants ≥18 years who had been hospitalised with laboratory-confirmed SARS-CoV-2 infection during the second and third wave between December 2020 and August 2021 underwent telephonic follow-up assessment up at one-month and three-months after hospital discharge. Participants were assessed using a standardised questionnaire for the evaluation of symptoms, functional status, health-related quality of life and occupational status. Multivariable logistic regression models were used to determine factors associated with PCC. Findings In total, 1,873 of 2,413 (78%) enrolled hospitalised COVID-19 participants were followed up at three-months after hospital discharge. Participants had a median age of 52 years (IQR 41-62) and 960 (51.3%) were women. At three-months follow-up, 1,249 (66.7%) participants reported one or more persistent COVID-related symptom(s), compared to 1,978/2,413 (82.1%) at one-month post-hospital discharge. The most common symptoms reported were fatigue (50.3%), shortness of breath (23.4%), confusion or lack of concentration (17.5%), headaches (13.8%) and problems seeing/blurred vision (10.1%). On multivariable analysis, factors associated with new or persistent symptoms following acute COVID-19 were age ≥65 years [adjusted odds ratio (aOR) 1.62;95%confidence interval (CI) 1.00-2.61];female sex (aOR 2.00;95% CI 1.51-2.65);mixed ethnicity (aOR 2.15;95% CI 1.26-3.66) compared to black ethnicity;requiring supplemental oxygen during admission (aOR 1.44;95% CI 1.06-1.97);ICU admission (aOR 1.87;95% CI 1.36-2.57);pre-existing obesity (aOR 1.44;95% CI 1.09-1.91);and the presence of ≥4 acute symptoms (aOR 1.94;95% CI 1.19-3.15) compared to no symptoms at onset. Interpretation The majority of COVID-19 survivors in this cohort of previously hospitalised participants reported persistent symptoms at three-months from hospital discharge, as well as a significant impact of PCC on their functional and occupational status. The large burden of PCC symptoms identified in this study emphasises the need for a national health strategy. This should include the development of clinical guidelines and training of health care workers, in identifying, assessing and caring for patients affected by PCC, establishment of multidisciplinary national health services, and provision of information and support to people who suffer from PCC.

2.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-329097

ABSTRACT

Background: Clinical severity of patients hospitalised with SARS-CoV-2 infection during the Omicron (fourth) wave was assessed and compared to trends in the D614G (first), Beta (second), and Delta (third) waves in South Africa. Methods: Weekly incidence of 30 laboratory-confirmed SARS-CoV-2 cases/100,000 population defined the start and end of each wave. Hospital admission data were collected through an active national COVID-19-specific surveillance programme. Disease severity was compared across waves by post-imputation random effect multivariable logistic regression models. Severe disease was defined as one or more of acute respiratory distress, supplemental oxygen, mechanical ventilation, intensive-care admission or death. Results: 335,219 laboratory-confirmed SARS-CoV-2 admissions were analysed, constituting 10.4% of 3,216,179 cases recorded during the 4 waves. In the Omicron wave, 8.3% of cases were admitted to hospital (52,038/629,617) compared to 12.9% (71,411/553,530) in the D614G, 12.6% (91,843/726,772) in the Beta and 10.0% (131,083/1,306,260) in the Delta waves (p<0.001). During the Omicron wave, 33.6% of admissions experienced severe disease compared to 52.3%, 63.4% and 63.0% in the D614G, Beta and Delta waves (p<0.001). The in-hospital case fatality ratio during the Omicron wave was 10.7%, compared to 21.5%, 28.8% and 26.4% in the D614G, Beta and Delta waves (p<0.001). Compared to the Omicron wave, patients had more severe clinical presentations in the D614G (adjusted odds ratio [aOR] 2.07;95% confidence interval [CI] 2.01-2.13), Beta (aOR 3.59;CI: 3.49-3.70) and Delta (aOR 3.47: CI: 3.38-3.57) waves. Conclusion: The trend of increasing cases and admissions across South Africa's first three waves shifted in Omicron fourth wave, with a higher and quicker peak but fewer admitted patients, who experienced less clinically severe illness and had a lower case-fatality ratio. Omicron marked a change in the SARS-CoV-2 epidemic curve, clinical profile and deaths in South Africa. Extrapolations to other populations should factor in differing vaccination and prior infection levels.

3.
N Engl J Med ; 386(14): 1314-1326, 2022 Apr 07.
Article in English | MEDLINE | ID: covidwho-1703992

ABSTRACT

BACKGROUND: The B.1.1.529 (omicron) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified on November 25, 2021, in Gauteng province, South Africa. Data regarding the seroprevalence of SARS-CoV-2 IgG in Gauteng before the fourth wave of coronavirus disease 2019 (Covid-19), in which the omicron variant was dominant, are needed. METHODS: We conducted a seroepidemiologic survey from October 22 to December 9, 2021, in Gauteng to determine the seroprevalence of SARS-CoV-2 IgG. Households included in a previous seroepidemiologic survey (conducted from November 2020 to January 2021) were contacted; to account for changes in the survey population, there was a 10% increase in the households contacted, with the use of the same sampling framework. Dried-blood-spot samples were tested for IgG against SARS-CoV-2 spike protein and nucleocapsid protein with the use of quantitative assays. We also evaluated Covid-19 epidemiologic trends in Gauteng, including cases, hospitalizations, recorded deaths, and excess deaths from the start of the pandemic through January 12, 2022. RESULTS: Samples were obtained from 7010 participants, of whom 1319 (18.8%) had received a Covid-19 vaccine. The seroprevalence of SARS-CoV-2 IgG ranged from 56.2% (95% confidence interval [CI], 52.6 to 59.7) among children younger than 12 years of age to 79.7% (95% CI, 77.6 to 81.5) among adults older than 50 years of age. Vaccinated participants were more likely to be seropositive for SARS-CoV-2 than unvaccinated participants (93.1% vs. 68.4%). Epidemiologic data showed that the incidence of SARS-CoV-2 infection increased and subsequently declined more rapidly during the fourth wave than it had during the three previous waves. The incidence of infection was decoupled from the incidences of hospitalization, recorded death, and excess death during the fourth wave, as compared with the proportions seen during previous waves. CONCLUSIONS: Widespread underlying SARS-CoV-2 seropositivity was observed in Gauteng before the omicron-dominant wave of Covid-19. Epidemiologic data showed a decoupling of hospitalizations and deaths from infections while omicron was circulating. (Funded by the Bill and Melinda Gates Foundation.).


Subject(s)
COVID-19 , Adult , Aged , Antibodies, Viral , COVID-19/epidemiology , COVID-19 Vaccines , Child , Humans , Immunoglobulin G , SARS-CoV-2 , Seroepidemiologic Studies , South Africa/epidemiology , Spike Glycoprotein, Coronavirus
4.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-314594

ABSTRACT

Introduction: We describe epidemiology and outcomes of confirmed SARS-CoV-2 infection and admissions among children <18 years in South Africa, an upper-middle income setting with high inequality. Methods: Laboratory and hospital COVID-19 surveillance data, 28 January - 19 September 2020 was used. Testing rates were calculated as number of tested for SARS-CoV-2 divided by population at risk;test positivity rates were calculated as positive tests divided by total number of tests. In-hospital case fatality ratio (CFR) was calculated based on hospitalized positive admissions with outcome data who died in-hospital and death was judged SARS-CoV-2 related by attending physician. Findings: 315,570 children aged <18 years were tested for SARS-CoV-2;representing 8.9% of all 3,548,738 tests and 1.6% of all children in the country. Of children tested, 46,137 (14.6%) were positive. Children made up 2.9% (n=2,007) of all SARS-CoV-2 positive admissions to sentinel hospitals. Among children, 47 died (2.6% case-fatality). In-hospital deaths were associated with male sex [adjusted odds ratio (aOR) 2.18 (95% confidence intervals (CI) 1.08 - 4.40)] vs female;age <1 year [aOR 4.11 (95% CI 1.08-15.54)], age 10-14 years [aOR 4.20 (95% CI1.07-16.44)], age 15-17 years [aOR 4.86 (95% 1.28 -18.51)] vs age 1-4 years;admission to a public hospital [aOR 5.07(95% 2.01 -12.76)] vs private hospital and ≥1 underlying conditions [aOR 12.09 (95% CI 4.19-34.89)] vs none Conclusions: Children with underlying conditions were at greater risk of severe SARS-CoV-2 outcomes. Children > 10 years and those with underlying conditions should be considered for increased testing and vaccination.

5.
Trop Med Infect Dis ; 7(2)2022 Jan 24.
Article in English | MEDLINE | ID: covidwho-1648874

ABSTRACT

This Special Issue focuses on recent global research on the current coronavirus (COVID-19) pandemic [...].

7.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-294124

ABSTRACT

Background: Globally, long-term care facilities (LTCFs) experienced a large burden of deaths during the COVID-19 pandemic. The study aimed to describe the temporal trends as well as the characteristics and risk factors for mortality among residents and staff who tested positive for SARS-CoV-2 in selected LTCFs across South Africa. Method: We analysed data reported to the DATCOV sentinel surveillance system by 45 LTCFs. Outbreaks in LTCFs were defined as large if more than one-third of residents and staff had been infected or there were more than 20 epidemiologically linked cases. Multivariable logistic regression was used to assess risk factors for mortality amongst LTCF residents. Results: : A total of 2,324 SARS-CoV-2 cases were reported from 5 March 2020 through 31 July 2021;1,504 (65%) were residents and 820 (35%) staff. Among LTCFs, 6 reported sporadic cases and 39 experienced outbreaks. Of those reporting outbreaks, 10 (26%) reported one and 29 (74%) reported more than one outbreak. There were 48 (66.7%) small outbreaks and 24 (33.3%) large outbreaks reported. There were 30 outbreaks reported in the first wave, 21 in the second wave and 15 in the third wave, with 6 outbreaks reporting between waves. There were 1,259 cases during the first COVID-19 wave, 362 during the second wave, and 299 during the current third wave. The case fatality ratio was 9% (138/1,504) among residents and 0.5% (4/820) among staff. On multivariable analysis, factors associated with SARS-CoV-2 mortality among LTCF residents were age 40-59 years, 60-79 years and ≥80 years compared to <40 years and being a resident in a LTCF in Free State or Northern Cape compared to Western Cape. Compared to pre-wave 1, there was a decreased risk of mortality in wave 1, post-wave 1, wave 2, post-wave 2 and wave 3. Conclusion: The analysis of SARS-CoV-2 cases in sentinel LTCFs in South Africa points to an encouraging trend of decreasing numbers of outbreaks, cases and risk for mortality since the first wave. LTCFs are likely to have learnt from international experience and adopted national protocols, which include improved measures to limit transmission and administer early and appropriate clinical care.

8.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-293600

ABSTRACT

Background: Globally, long-term care facilities (LTCFs) experienced a large burden of deaths during the COVID-19 pandemic. The study aimed to describe the temporal trends as well as the characteristics and risk factors for mortality among residents and staff who tested positive for SARS-CoV-2 in selected LTCFs across South Africa. Method: We analysed data reported to the DATCOV sentinel surveillance system by 45 LTCFs. Outbreaks in LTCFs were defined as large if more than one-third of residents and staff had been infected or there were more than 20 epidemiologically linked cases. Multivariable logistic regression was used to assess risk factors for mortality amongst LTCF residents. Results: : A total of 2,324 SARS-CoV-2 cases were reported from 5 March 2020 through 31 July 2021;1,504 (65%) were residents and 820 (35%) staff. Among LTCFs, 6 reported sporadic cases and 39 experienced outbreaks. Of those reporting outbreaks, 10 (26%) reported one and 29 (74%) reported more than one outbreak. There were 48 (66.7%) small outbreaks and 24 (33.3%) large outbreaks reported. There were 30 outbreaks reported in the first wave, 21 in the second wave and 15 in the third wave, with 6 outbreaks reporting between waves. There were 1,259 cases during the first COVID-19 wave, 362 during the second wave, and 299 during the current third wave. The case fatality ratio was 9% (138/1,504) among residents and 0.5% (4/820) among staff. On multivariable analysis, factors associated with SARS-CoV-2 mortality among LTCF residents were age 40-59 years, 60-79 years and ≥80 years compared to <40 years and being a resident in a LTCF in Free State or Northern Cape compared to Western Cape. Compared to pre-wave 1, there was a decreased risk of mortality in wave 1, post-wave 1, wave 2, post-wave 2 and wave 3. Conclusion: The analysis of SARS-CoV-2 cases in sentinel LTCFs in South Africa points to an encouraging trend of decreasing numbers of outbreaks, cases and risk for mortality since the first wave. LTCFs are likely to have learnt from international experience and adopted national protocols, which include improved measures to limit transmission and administer early and appropriate clinical care.

10.
Influenza Other Respir Viruses ; 16(1): 34-47, 2022 01.
Article in English | MEDLINE | ID: covidwho-1526373

ABSTRACT

INTRODUCTION: We describe epidemiology and outcomes of confirmed SARS-CoV-2 infection and positive admissions among children <18 years in South Africa, an upper-middle income setting with high inequality. METHODS: Laboratory and hospital COVID-19 surveillance data, 28 January - 19 September 2020 was used. Testing rates were calculated as number of tested for SARS-CoV-2 divided by population at risk; test positivity rates were calculated as positive tests divided by total number of tests. In-hospital case fatality ratio (CFR) was calculated based on hospitalized positive admissions with outcome data who died in-hospital and whose death was judged SARS-CoV-2 related by attending physician. FINDINGS: 315 570 children aged <18 years were tested for SARS-CoV-2; representing 8.9% of all 3 548 738 tests and 1.6% of all children in the country. Of children tested, 46 137 (14.6%) were positive. Children made up 2.9% (n = 2007) of all SARS-CoV-2 positive admissions to sentinel hospitals. Among children, 47 died (2.6% case-fatality). In-hospital deaths were associated with male sex [adjusted odds ratio (aOR) 2.18 (95% confidence intervals [CI] 1.08-4.40)] vs female; age <1 year [aOR 4.11 (95% CI 1.08-15.54)], age 10-14 years [aOR 4.20 (95% CI1.07-16.44)], age 15-17 years [aOR 4.86 (95% 1.28-18.51)] vs age 1-4 years; admission to a public hospital [aOR 5.07(95% 2.01-12.76)] vs private hospital and ≥1 underlying conditions [aOR 12.09 (95% CI 4.19-34.89)] vs none. CONCLUSIONS: Children with underlying conditions were at greater risk of severe SARS-CoV-2 outcomes. Children > 10 years, those in certain provinces and those with underlying conditions should be considered for increased testing and vaccination.


Subject(s)
COVID-19 , Adolescent , Child , Child, Preschool , Female , Hospitals , Humans , Infant , Male , Risk Factors , SARS-CoV-2 , South Africa/epidemiology
12.
Lancet Glob Health ; 9(9): e1216-e1225, 2021 09.
Article in English | MEDLINE | ID: covidwho-1368858

ABSTRACT

BACKGROUND: The first wave of COVID-19 in South Africa peaked in July, 2020, and a larger second wave peaked in January, 2021, in which the SARS-CoV-2 501Y.V2 (Beta) lineage predominated. We aimed to compare in-hospital mortality and other patient characteristics between the first and second waves. METHODS: In this prospective cohort study, we analysed data from the DATCOV national active surveillance system for COVID-19 admissions to hospital from March 5, 2020, to March 27, 2021. The system contained data from all hospitals in South Africa that have admitted a patient with COVID-19. We used incidence risk for admission to hospital and determined cutoff dates to define five wave periods: pre-wave 1, wave 1, post-wave 1, wave 2, and post-wave 2. We compared the characteristics of patients with COVID-19 who were admitted to hospital in wave 1 and wave 2, and risk factors for in-hospital mortality accounting for wave period using random-effect multivariable logistic regression. FINDINGS: Peak rates of COVID-19 cases, admissions, and in-hospital deaths in the second wave exceeded rates in the first wave: COVID-19 cases, 240·4 cases per 100 000 people vs 136·0 cases per 100 000 people; admissions, 27·9 admissions per 100 000 people vs 16·1 admissions per 100 000 people; deaths, 8·3 deaths per 100 000 people vs 3·6 deaths per 100 000 people. The weekly average growth rate in hospital admissions was 20% in wave 1 and 43% in wave 2 (ratio of growth rate in wave 2 compared with wave 1 was 1·19, 95% CI 1·18-1·20). Compared with the first wave, individuals admitted to hospital in the second wave were more likely to be age 40-64 years (adjusted odds ratio [aOR] 1·22, 95% CI 1·14-1·31), and older than 65 years (aOR 1·38, 1·25-1·52), compared with younger than 40 years; of Mixed race (aOR 1·21, 1·06-1·38) compared with White race; and admitted in the public sector (aOR 1·65, 1·41-1·92); and less likely to be Black (aOR 0·53, 0·47-0·60) and Indian (aOR 0·77, 0·66-0·91), compared with White; and have a comorbid condition (aOR 0·60, 0·55-0·67). For multivariable analysis, after adjusting for weekly COVID-19 hospital admissions, there was a 31% increased risk of in-hospital mortality in the second wave (aOR 1·31, 95% CI 1·28-1·35). In-hospital case-fatality risk increased from 17·7% in weeks of low admission (<3500 admissions) to 26·9% in weeks of very high admission (>8000 admissions; aOR 1·24, 1·17-1·32). INTERPRETATION: In South Africa, the second wave was associated with higher incidence of COVID-19, more rapid increase in admissions to hospital, and increased in-hospital mortality. Although some of the increased mortality can be explained by admissions in the second wave being more likely in older individuals, in the public sector, and by the increased health system pressure, a residual increase in mortality of patients admitted to hospital could be related to the new Beta lineage. FUNDING: DATCOV as a national surveillance system is funded by the National Institute for Communicable Diseases and the South African National Government.


Subject(s)
COVID-19/mortality , COVID-19/therapy , Hospital Mortality/trends , Hospitalization/statistics & numerical data , Adult , Aged , COVID-19/epidemiology , Female , Humans , Male , Middle Aged , Prospective Studies , Risk Factors , South Africa/epidemiology
13.
EClinicalMedicine ; 39: 101072, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1351633

ABSTRACT

BACKGROUND: We describe the epidemiology of COVID-19 in South Africa following importation and during implementation of stringent lockdown measures. METHODS: Using national surveillance data including demographics, laboratory test data, clinical presentation, risk exposures (travel history, contacts and occupation) and outcomes of persons undergoing COVID-19 testing or hospitalised with COVID-19 at sentinel surveillance sites, we generated and interpreted descriptive statistics, epidemic curves, and initial reproductive numbers (Rt). FINDINGS: From 4 March to 30 April 2020, 271,670 SARS-CoV-2 PCR tests were performed (462 tests/100,000 persons). Of these, 7,892 (2.9%) persons tested positive (median age 37 years (interquartile range 28-49 years), 4,568 (58%) male, cumulative incidence of 13.4 cases/100,000 persons). Hospitalization records were found for 1,271 patients (692 females (54%)) of whom 186 (14.6%) died. Amongst 2,819 cases with data, 489/2819 (17.3%) travelled internationally within 14 days prior to diagnosis, mostly during March 2020 (466 (95%)). Cases diagnosed in April compared with March were younger (median age, 37 vs. 40 years), less likely female (38% vs. 53%) and resident in a more populous province (98% vs. 91%). The national initial Rt was 2.08 (95% confidence interval (CI): 1.71-2.51). INTERPRETATION: The first eight weeks following COVID-19 importation were characterised by early predominance of imported cases and relatively low mortality and transmission rates. Despite stringent lockdown measures, the second month following importation was characterised by community transmission and increasing disease burden in more populous provinces.

14.
Lancet HIV ; 8(9): e554-e567, 2021 09.
Article in English | MEDLINE | ID: covidwho-1340936

ABSTRACT

BACKGROUND: The interaction between COVID-19, non-communicable diseases, and chronic infectious diseases such as HIV and tuberculosis is unclear, particularly in low-income and middle-income countries in Africa. South Africa has a national HIV prevalence of 19% among people aged 15-49 years and a tuberculosis prevalence of 0·7% in people of all ages. Using a nationally representative hospital surveillance system in South Africa, we aimed to investigate the factors associated with in-hospital mortality among patients with COVID-19. METHODS: In this cohort study, we used data submitted to DATCOV, a national active hospital surveillance system for COVID-19 hospital admissions, for patients admitted to hospital with laboratory-confirmed SARS-CoV-2 infection between March 5, 2020, and March 27, 2021. Age, sex, race or ethnicity, and comorbidities (hypertension, diabetes, chronic cardiac disease, chronic pulmonary disease and asthma, chronic renal disease, malignancy in the past 5 years, HIV, and past and current tuberculosis) were considered as risk factors for COVID-19-related in-hospital mortality. COVID-19 in-hospital mortality, the main outcome, was defined as a death related to COVID-19 that occurred during the hospital stay and excluded deaths that occurred because of other causes or after discharge from hospital; therefore, only patients with a known in-hospital outcome (died or discharged alive) were included. Chained equation multiple imputation was used to account for missing data and random-effects multivariable logistic regression models were used to assess the role of HIV status and underlying comorbidities on COVID-19 in-hospital mortality. FINDINGS: Among the 219 265 individuals admitted to hospital with laboratory-confirmed SARS-CoV-2 infection and known in-hospital outcome data, 51 037 (23·3%) died. Most commonly observed comorbidities among individuals with available data were hypertension in 61 098 (37·4%) of 163 350, diabetes in 43 885 (27·4%) of 159 932, and HIV in 13 793 (9·1%) of 151 779. Tuberculosis was reported in 5282 (3·6%) of 146 381 individuals. Increasing age was the strongest predictor of COVID-19 in-hospital mortality. Other factors associated were HIV infection (adjusted odds ratio 1·34, 95% CI 1·27-1·43), past tuberculosis (1·26, 1·15-1·38), current tuberculosis (1·42, 1·22-1·64), and both past and current tuberculosis (1·48, 1·32-1·67) compared with never tuberculosis, as well as other described risk factors for COVID-19, such as male sex; non-White race; underlying hypertension, diabetes, chronic cardiac disease, chronic renal disease, and malignancy in the past 5 years; and treatment in the public health sector. After adjusting for other factors, people with HIV not on antiretroviral therapy (ART; adjusted odds ratio 1·45, 95% CI 1·22-1·72) were more likely to die in hospital than were people with HIV on ART. Among people with HIV, the prevalence of other comorbidities was 29·2% compared with 30·8% among HIV-uninfected individuals. Increasing number of comorbidities was associated with increased COVID-19 in-hospital mortality risk in both people with HIV and HIV-uninfected individuals. INTERPRETATION: Individuals identified as being at high risk of COVID-19 in-hospital mortality (older individuals and those with chronic comorbidities and people with HIV, particularly those not on ART) would benefit from COVID-19 prevention programmes such as vaccine prioritisation as well as early referral and treatment. FUNDING: South African National Government.


Subject(s)
COVID-19/mortality , HIV Infections/epidemiology , Tuberculosis/epidemiology , Anti-Retroviral Agents/therapeutic use , COVID-19/epidemiology , Cohort Studies , Comorbidity , Female , HIV Infections/drug therapy , Hospital Mortality , Humans , Male , Prevalence , Risk Factors , SARS-CoV-2 , South Africa/epidemiology
16.
Trans R Soc Trop Med Hyg ; 115(2): 182-184, 2021 01 28.
Article in English | MEDLINE | ID: covidwho-1307557

ABSTRACT

The forthcoming World Health Organization road map for neglected tropical diseases (NTDs) 2021-2030 recognises the complexity surrounding control and elimination of these 20 diseases of poverty. It emphasises the need for a paradigm shift from disease-specific interventions to holistic cross-cutting approaches coordinating with adjacent disciplines. The One Health approach exemplifies this shift, extending beyond a conventional model of zoonotic disease control to consider the interactions of human and animal health systems within their shared environment and the wider social and economic context. This approach can also promote sustainability and resilience within these systems. To achieve the global ambition on NTD elimination and control, political will, along with contextualised innovative scientific strategies, is required.


Subject(s)
One Health , Tropical Medicine , Animals , Global Health , Humans , Neglected Diseases/prevention & control , World Health Organization
20.
Int J Infect Dis ; 96: 233-239, 2020 Jul.
Article in English | MEDLINE | ID: covidwho-133487

ABSTRACT

AIM: The purpose of this perspective is to review the options countries have to exit the draconian "lockdowns" in a carefully staged manner. METHODS: Experts from different countries experiencing Corona Virus Infectious Disease 2019 (COVID-19) reviewed evidence and country-specific approaches and the results of their interventions. RESULTS: Three factors are essential: 1. Reintroduction from countries with ongoing community transmission; 2. The need for extensive testing capacity and widespread community testing, and 3. An adequate supply of personal protective equipment, PPE, to protect health care workers. Discussed at length are lifting physical distancing, how to open manufacturing and construction, logistics, and the opening of higher educational institutions and schools. The use of electronic surveillance is considered. CONCLUSION: Each country should decide on the best path forward. However, we can learn from each other, and the approaches are, in reality, very similar.


Subject(s)
Betacoronavirus , Coronavirus Infections/prevention & control , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , COVID-19 , COVID-19 Testing , Clinical Laboratory Techniques , Coronavirus Infections/diagnosis , Coronavirus Infections/transmission , Delivery of Health Care , Humans , Infectious Disease Transmission, Patient-to-Professional/prevention & control , Personal Protective Equipment , Pneumonia, Viral/diagnosis , Pneumonia, Viral/transmission , SARS-CoV-2 , Travel
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