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1.
Front Public Health ; 10: 834592, 2022.
Article in English | MEDLINE | ID: covidwho-1952773

ABSTRACT

In Ethiopia, multiple waves of the COVID-19 epidemic have been observed. So far, no studies have investigated the characteristics of the waves of epidemic waves in the country. Identifying the epidemic trend in Ethiopia will inform future prevention and control of COVID-19. This study aims to identify the early indicators and the characteristics of multiple waves of the COVID-19 epidemics and their impact on the overall epidemic size in Ethiopia. We employed the Jointpoint software to identify key epidemic characteristics in the early phase of the COVID-19 epidemic and a simple logistic growth model to identify epidemic characteristics of its subsequent waves. Among the first 100 reported cases in Ethiopia, we identified a slow-growing phase (0.37 [CI: 0.10-0.78] cases/day), which was followed by a fast-growing phase (1.18 [0.50-2.00] cases/day). The average turning point from slow to fast-growing phase was at 18 days after first reported. We identified two subsequent waves of COVID-19 in Ethiopia during 03/2020-04/2021. We estimated the number of COVID-19 cases that occurred during the second wave (157,064 cases) was >2 times more than the first (60,016 cases). The second wave's duration was longer than the first (116 vs. 96 days). As of April 30th, 2021, the overall epidemic size in Ethiopia was 794/100,000, ranging from 1,669/100,000 in the Harari region to 40/100,000 in the Somali region. The epidemic size was significantly and positively correlated with the day of the phase turning point (r = 0.750, P = 0.008), the estimated number of cases in wave one (r = 0.854, P < 0.001), and wave two (r = 0.880, P < 0.001). The second wave of COVID-19 in Ethiopia is far greater, and its duration is longer than the first. Early phase turning point and case numbers in the subsequent waves predict its overall epidemic size.


Subject(s)
COVID-19 , Epidemics , COVID-19/epidemiology , Ethiopia/epidemiology , Humans
2.
Front Immunol ; 13: 864838, 2022.
Article in English | MEDLINE | ID: covidwho-1924099

ABSTRACT

Introduction: During the COVID-19 pandemic, people living with HIV (PLWH) were considered to be at risk of worse COVID-19 outcomes once infected. However, the existing evidence is inconsistent. This systematic review and meta-analysis aimed to compare the risk of SARS-CoV-2 infection, severe COVID-19 symptoms, and mortality among PLWH and patients without HIV. Method: The articles included studies published in PubMed, Medline, Embase, and Cochrane between December 1, 2019, and December 1, 2021. We included the original studies published in English focusing on observational studies assessing the risk of SARS-CoV-2 infection, severe COVID-19 symptoms, and mortality among PLWH. Four independent reviewers extracted data. STrengthening the Reporting of OBservational studies in Epidemiology-Modified (STROBE-M) checklist was used for quality assessment. For the results with heterogeneity I2 >75%, a random-effects model was employed. Otherwise, a fixed-effects model was used. The risk of SARS-CoV-2 infection, severe COVID-19 symptoms, and mortality were compared with and without HIV. Results: We included a total of 32 studies and 71,779,737 study samples, of whom 797,564 (1.11%) were PLWH. Compared with COVID-19 patients without HIV infection, PLWH had comparable risk of SARS-CoV-2 infection (adjusted Risk Ratio=1.07, 95% CI: 0.53-2.16, I2 = 96%, study n=6, n=20,199,805) and risk of developing severe COVID-19 symptoms (aRR=1.06, 95% CI: 0.97-1.16, I2 = 75%, n=10, n=2,243,370). PLWH, if infected with SARS-CoV-2, were found to have an increased risk of mortality compared with people without HIV (aRR=1.30, 95% CI: 1.09-1.56, I2 = 76%, study n=16, n=71,032,659). This finding was consistent across different subgroup analyses. Conclusion: PLWH are at increased risk of COVID-19 related mortality once infected. The local health system should, on the one hand, strengthen COVID-19 prevention and clinical management among PLWH to avoid infection and, on the other hand, sustain the HIV care continuum for PLWH for HIV management.


Subject(s)
COVID-19 , HIV Infections , HIV Seropositivity , HIV-1 , HIV Infections/drug therapy , Humans , Pandemics , SARS-CoV-2
3.
Pathogens ; 11(5)2022 May 13.
Article in English | MEDLINE | ID: covidwho-1855736

ABSTRACT

It is still uncertain how the epidemic characteristics of COVID-19 in its early phase and subsequent waves contributed to the pre-delta epidemic size in the United States. We identified the early and subsequent characteristics of the COVID-19 epidemic and the correlation between these characteristics and the pre-delta epidemic size. Most (96.1% (49/51)) of the states entered a fast-growing phase before the accumulative number of cases reached (30). The days required for the number of confirmed cases to increase from 30 to 100 was 5.6 (5.1-6.1) days. As of 31 March 2021, all 51 states experienced at least 2 waves of COVID-19 outbreaks, 23.5% (12/51) experienced 3 waves, and 15.7% (8/51) experienced 4 waves, the epidemic size of COVID-19 was 19,275-3,669,048 cases across the states. The pre-delta epidemic size was significantly correlated with the duration from 30 to 100 cases (p = 0.003, r = -0.405), the growth rate of the fast-growing phase (p = 0.012, r = 0.351), and the peak cases in the subsequent waves (K1 (p < 0.001, r = 0.794), K2 (p < 0.001, r = 0.595), K3 (p < 0.001, r = 0.977), and K4 (p = 0.002, r = 0.905)). We observed that both early and subsequent epidemic characteristics contribute to the pre-delta epidemic size of COVID-19. This identification is important to the prediction of the emerging viral infectious diseases in the primary stage.

4.
BMC Pulm Med ; 21(1): 64, 2021 Feb 24.
Article in English | MEDLINE | ID: covidwho-1102335

ABSTRACT

OBJECTIVES: We aimed to identify high-risk factors for disease progression and fatality for coronavirus disease 2019 (COVID-19) patients. METHODS: We enrolled 2433 COVID-19 patients and used LASSO regression and multivariable cause-specific Cox proportional hazard models to identify the risk factors for disease progression and fatality. RESULTS: The median time for progression from mild-to-moderate, moderate-to-severe, severe-to-critical, and critical-to-death were 3.0 (interquartile range: 1.8-5.5), 3.0 (1.0-7.0), 3.0 (1.0-8.0), and 6.5 (4.0-16.3) days, respectively. Among 1,758 mild or moderate patients at admission, 474 (27.0%) progressed to a severe or critical stage. Age above 60 years, elevated levels of blood glucose, respiratory rate, fever, chest tightness, c-reaction protein, lactate dehydrogenase, direct bilirubin, and low albumin and lymphocyte count were significant risk factors for progression. Of 675 severe or critical patients at admission, 41 (6.1%) died. Age above 74 years, elevated levels of blood glucose, fibrinogen and creatine kinase-MB, and low plateleta count were significant risk factors for fatality. Patients with elevated blood glucose level were 58% more likely to progress and 3.22 times more likely to die of COVID-19. CONCLUSIONS: Older age, elevated glucose level, and clinical indicators related to systemic inflammatory responses and multiple organ failures, predict both the disease progression and the fatality of COVID-19 patients.


Subject(s)
Blood Glucose/metabolism , COVID-19/blood , COVID-19/mortality , Disease Progression , Hyperglycemia/blood , Adult , Age Factors , Aged , Aged, 80 and over , Bilirubin/blood , C-Reactive Protein/metabolism , China/epidemiology , Critical Illness , Female , Fever/virology , Humans , Hyperglycemia/complications , L-Lactate Dehydrogenase/blood , Lymphocyte Count , Male , Middle Aged , Proportional Hazards Models , Retrospective Studies , SARS-CoV-2 , Serum Albumin/metabolism , Time Factors
6.
Innovation (N Y) ; 1(1): 100006, 2020 May 21.
Article in English | MEDLINE | ID: covidwho-833425

ABSTRACT

BACKGROUND: The Chinese government implemented a metropolitan-wide quarantine of Wuhan city on 23rd January 2020 to curb the epidemic of the coronavirus COVID-19. Lifting of this quarantine is imminent. We modelled the effects of two key health interventions on the epidemic when the quarantine is lifted. METHODS: We constructed a compartmental dynamic model to forecast the trend of the COVID-19 epidemic at different quarantine lifting dates and investigated the impact of different rates of public contact and facial mask usage on the epidemic. RESULTS: We projected a declining trend of the COVID-19 epidemic if the current quarantine strategy continues, and Wuhan would record the last new confirmed cases in late April 2020. At the end of the epidemic, 65,733 (45,722-99,015) individuals would be infected by the virus, among which 16,166 (11,238-24,603, 24.6%) were through public contacts, 45,996 (31,892-69,565, 69.7%) through household contact, and 3,571 (2,521-5,879, 5.5%) through hospital contacts (including 778 (553-1,154) non-COVID-19 patients and 2,786 (1,969-4,791) medical staff). A total of 2,821 (1,634-6,361) would die of COVID-19 related pneumonia in Wuhan. Early quarantine lifting on 21st March is viable only if Wuhan residents sustain a high facial mask usage of ≥85% and a pre-quarantine level public contact rate. Delaying city resumption to mid/late April would relax the requirement of facial mask usage to ≥75% at the same contact rate. CONCLUSIONS: The prevention of a second epidemic is viable after the metropolitan-wide quarantine is lifted but requires a sustaining high facial mask usage and a low public contact rate.

7.
Innovation (N Y) ; 1(3): 100049, 2020 Nov 25.
Article in English | MEDLINE | ID: covidwho-807209
8.
PLoS Med ; 17(7): e1003240, 2020 07.
Article in English | MEDLINE | ID: covidwho-661234

ABSTRACT

Yuming Guo and colleagues discuss the research by Teslya et al that highlights the importance of personal preventative measures in avoiding a second wave of the COVID-19 epidemic.


Subject(s)
Betacoronavirus , Coronavirus Infections , Infection Control , Pandemics , Pneumonia, Viral/epidemiology , COVID-19 , Government , Humans , Infection Control/methods , Quarantine , SARS-CoV-2
9.
Int J Infect Dis ; 97: 219-224, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-636709

ABSTRACT

OBJECTIVES: The mostly-resolved first wave of the COVID-19 epidemic in China provided a unique opportunity to investigate how the initial characteristics of the COVID-19 outbreak predict its subsequent magnitude. METHODS: We collected publicly available COVID-19 epidemiological data from 436 Chinese cities from 16th January-15th March 2020. Based on 45 cities that reported >100 confirmed cases, we examined the correlation between early-stage epidemic characteristics and subsequent epidemic magnitude. RESULTS: We identified a transition point from a slow- to a fast-growing phase for COVID-19 at 5.5 (95% CI, 4.6-6.4) days after the first report, and 30 confirmed cases marked a critical threshold for this transition. The average time for the number of confirmed cases to increase from 30 to 100 (time from 30-to-100) was 6.6 (5.3-7.9) days, and the average case-fatality rate in the first 100 confirmed cases (CFR-100) was 0.8% (0.2-1.4%). The subsequent epidemic size per million population was significantly associated with both of these indicators. We predicted a ranking of epidemic size in the cities based on these two indicators and found it highly correlated with the actual classification of epidemic size. CONCLUSIONS: Early epidemic characteristics are important indicators for the size of the entire epidemic.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , COVID-19 , China/epidemiology , Cities/epidemiology , Disease Outbreaks , Epidemics , Humans , Pandemics , SARS-CoV-2
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