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Kisely S, Warren N, McMahon L, Dalais C, Henry I, Siskind D. Occurrence, prevention, and management of the psychological effects of emerging virus outbreaks on healthcare workers: rapid review and meta-analysis. BMA Survey Finds Doctors' Lives Still at Risk Despite Government Pledges on PPE. British Medical Association, 7 April 2020. https://www.bma.org.uk/bma-media-centre/ bma-survey-finds-doctors-lives-still-at-risk-despitegovernment-pledges-on-ppe (28 July 2020, date last accessed). [Extracted from the article]

Background: In 2020, SARS-CoV-2 and the COVID-19 pandemic had a huge impact on the access to and provision of ART treatments. Gradually, knowledge of the virus and its transmission has become available, allowing ART activities to resume. Still, questions on the impact of the virus on human gametes and fertility remain.Objective and Rationale: This article summarizes published data, aiming to clarify the impact of SARS-CoV-2 and the COVID-19 disease on human fertility and assisted reproduction, as well as the impact of vaccination, and from this, provide answers to questions that are relevant for people contemplating pregnancy and for health care professionals.Search Methods: PUBMED/MEDLINE and the WHO COVID-19 database were searched from inception to 5 October 2022 with search terms focusing on 'SARS-CoV-2' and gametes, embryos, reproductive function, fertility and ART. Non-English studies and papers published prior to 2020 were excluded, as well as reviews and non-peer reviewed publications. Full papers were assessed for relevance and quality, where feasible.Outcomes: From the 148 papers included, the following observations were made. The SARS-CoV-2-binding proteins, angiotensin-converting enzyme 2 (ACE2) and type II transmembrane serine protease (TMPRSS2), are expressed in the testis, but co-expression remains to be proven. There is some evidence of SARS-CoV-2 RNA in the ejaculate of COVID-19 patients with severe disease, but not in those with mild/moderate disease. SARS-CoV-2 infection can impair spermatogenesis, but this seems to resolve after one spermatogenic cycle. Testosterone levels seem to be lower during and after COVID-19, but long-term data are lacking; disease severity may be associated with testosterone levels. COVID-19 cannot be considered a sexually transmitted disease. There is no co-expression of ACE2 and TMPRSS2 in the myometrium, uterus, ovaries or fallopian tubes. Oocytes seem to have the receptors and protease machinery to be susceptible to SARS-CoV-2 infection; however, viral RNA in oocytes has not been detected so far. Women contemplating pregnancy following COVID-19 may benefit from screening for thyroid dysfunction. There is a possible (transient) impact of COVID-19 on menstrual patterns. Embryos, and particularly late blastocysts, seem to have the machinery to be susceptible to SARS-CoV-2 infection. Most studies have not reported a significant impact of COVID-19 on ovarian reserve, ovarian function or follicular fluid parameters. Previous asymptomatic or mild SARS-CoV-2 infection in females does not seem to negatively affect laboratory and clinical outcomes of ART. There are no data on the minimum required interval, if any, between COVID-19 recovery and ART. There is no evidence of a negative effect of SARS-CoV-2 vaccination on semen parameters or spermatogenesis, ovarian function, ovarian reserve or folliculogenesis. A transient effect on the menstrual cycle has been documented. Despite concerns, cross reactivity between anti-SARS-CoV-2 spike protein antibodies and Syncytin-1, an essential protein in human implantation, is absent. There is no influence of mRNA SARS-CoV-2 vaccine on patients' performance during their immediate subsequent ART cycle. Pregnancy rates post-vaccination are similar to those in unvaccinated patients.Wider Implications: This review highlights existing knowledge on the impact of SARS-CoV-2 infection or COVID-19 on fertility and assisted reproduction, but also identifies gaps and offers suggestions for future research. The knowledge presented should help to provide evidence-based advice for practitioners and couples contemplating pregnancy alike, facilitating informed decision-making in an environment of significant emotional turmoil. [ABSTRACT FROM AUTHOR]

More than 50 000 papers have been published about COVID-19 since the beginning of 2020 and several hundred new papers continue to be published every day. This incredible rate of scientific productivity leads to information overload, making it difficult for researchers, clinicians and public health officials to keep up with the latest findings. Automated text mining techniques for searching, reading and summarizing papers are helpful for addressing information overload. In this review, we describe the many resources that have been introduced to support text mining applications over the COVID-19 literature; specifically, we discuss the corpora, modeling resources, systems and shared tasks that have been introduced for COVID-19. We compile a list of 39 systems that provide functionality such as search, discovery, visualization and summarization over the COVID-19 literature. For each system, we provide a qualitative description and assessment of the system's performance, unique data or user interface features and modeling decisions. Many systems focus on search and discovery, though several systems provide novel features, such as the ability to summarize findings over multiple documents or linking between scientific articles and clinical trials. We also describe the public corpora, models and shared tasks that have been introduced to help reduce repeated effort among community members; some of these resources (especially shared tasks) can provide a basis for comparing the performance of different systems. Finally, we summarize promising results and open challenges for text mining the COVID-19 literature. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) has been a global disaster, with over 746,312 confirmed cases and still counting in Indonesia, especially Jakarta, which has about 50 per cent asymptomatic confirmed cases. This paper aims to investigate the persistent factors of COVID-19 diagnosis using four scenarios of asymptomatic inclusion. We use Bayesian Logistic Regression to identify the factors of COVID-19 positivity, which can address issues in the traditional approach such as overfitting and uncertainty. This study discovers three main findings: (1) COVID-19 can infect people regardless of age; (2) Among twelve symptoms of coronavirus (COVID-19), five symptoms increase the COVID-19 likelihood, and two symptoms decrease the possibility of COVID-19 infection; and (3) From an epidemiological perspective, the contact history rises the probability of COVID-19, while healthcare workers and people who did travel are less likely to become infected from COVID-19. Therefore given this study, it is essential to be attentive to the people who have the symptoms and contact history. Surprisingly, health care workers and travelers who apply health protocols strictly according to the rules have a low risk of COVID19 infection. [ABSTRACT FROM AUTHOR]

Background The COVID-19 outbreak is increasing and spreading rapidly globally, with over 20 million cases and 800, 000 thousand deaths reported in 216 countries as of 28th August 2020. Since the report of the index case in Nigeria in February 2020 by the Nigeria Center for Disease Control (NCDC), daily records of confirmed cases have been reported in all states in the country. On 3rd April 2020, an outbreak of Coronavirus disease-2019 (COVID-19) was confirmed in Ondo State, Southwest Nigeria. Field investigations were conducted by the State Ministry of Health (MoH) to identify and confirm additional cases. This paper provides the outcome of the epidemiological investigation of the outbreak to further guide outbreak response activities. Methods Outbreak settings Ondo State is in the South-West Zone of Nigeria with her capital at Akure. The State is situated between longitudes 40 151E and 60 001E of the Greenwich median and latitudes 50 451N and 70 451 N, which are to the North of the equator in the Southwestern geopolitical zones of the country. Field Investigation The investigation was conducted as part of outbreak control and response measures hence permission to conduct the study was obtained from the Ondo State Ministry of Health (OSMoH). Following an alert from clinicians at a government-owned Hospital, Akure, Ondo State on 30 March 2020, the index case of COVID-19, a 34-year-old male with recent travel history to India was investigated. He arrived at Ondo State on 21st March 2020 and presented at the hospital with cough, sore throat and running nose with the onset of symptoms on 23rd March 2020. The State public health emergency Rapid Response Team (RRT) comprising of Commissioner for Health, State Epidemiologist, State and LGA surveillance officers, and health development partners in the state visited the hospital to investigate and implement public health response. Nasopharygeal and oropharyngeal samples were collected and tested for COVID-19, and returned positive from the national reference laboratory on the 3rd of April 2020. Operational definitions During the onset of the outbreak, three categories of case definitions for COVID-19 were used to guide the outbreak investigations according to the Nigeria Center for Diseases Control (NCDC) guidelines. Suspect case: (1) This is a patient with acute respiratory illness (fever and at least one sign/ symptom of respiratory disease (e.g. cough, shortness of breath) and a history of travel to or residence in a country/area or territory reporting local transmission of COVID-19 disease during the 14 days prior to symptom onset; (2) or a patient/health care worker with any acute respiratory illness and has been in contact with a confirmed COVID-19 case in the last 14 days prior to the onset of symptoms; (3) or a patient with a severe acute respiratory infection (fever and at least one sign/symptom of respiratory disease (e.g. cough, shortness of breath) and requiring hospitalization and with no other aetiology that fully explains the clinical presentation; (4) or a case for whom testing for COVID-19 is inconclusive. Confirmed case: A person with laboratory confirmation of COVID-19 infection, irrespective of clinical signs and symptoms. Probable case: Any suspected case for whom testing for COVID-19 is indeterminate test result or for whom testing was positive on a pan-coronavirus assay Data analysis The State COVID-19 line-list and case investigation forms of all COVID-19 cases from 19th March to 9th August 2020 were retrieved from the state disease surveillance unit, information on key variables were extracted and exported into SPSS version 20 and analyzed. Descriptive statistics such as frequency table, mean (standard deviation) and charts were used to describe key variables including LGA, age, sex, occupation and education and clinical conditions of cases. The week of report of cases and outcomes were used to generate the epidemic curve. The Chi-square test was used to compare categorical variables including the socio-demographic characteristics, clinical condition and outcome of cases. Two-sided P-values <0.05 were considered statistically significant. Results Socio-demographic characteristics of cases A total of 4353 suspected cases were reported and tested for COVID-19, of which 1316 COVID-19 cases were confirmed, with a case fatality rate of 2.2% recorded in 7 of the 17 Local Government Areas that reported at least a confirmed case (Figure 1). Most of the confirmed cases (1169; 88.8%), resides in urban areas (LGAs) (Table 1). Majority [1110 (84.3%)] were within the age group 20 to 59 years, with a mean age of 37.8 ±14.8 years. Males (713; 54.2%) were more affected compare to females (603; 45.8). More than three quarters (1009; 76.7%) of the cases had a tertiary level of education. Health care workers (404; 30.7%) were most affected compared to other professionals as shown in Table 1. 1170 Figure 1: Open in new tab Download slide Distribution of suspected and confirmed COVID-19 cases in Ondo state, March to August 2020 1170 Figure 1: Open in new tab Download slide Distribution of suspected and confirmed COVID-19 cases in Ondo state, March to August 2020 1170 Table 1: Socio-demographic characteristics of respondents N = 1316 Variable.  Frequency.  Percentage.  Age in years       <5  18  1.4  5-19  84  6.4  20-39  666  50.6  40-59  444  33.7  60-79  96  7.3  ≥80  8  0.6  Gender       Male  713  54.2  Female  603  45.8  Location of cases       Rural  147  11.2  Urban  1169  88.8  Type of Education       None  15  1.1  Nursery  8  0.6  Primary  80  6.1  Secondary  204  15.5  Tertiary  1009  76.7  Occupation       Health workers  404  30.7  Businessman and woman  225  17.1  Civil servant  168  12.8  Others  182  13.8  Pupil/Student  129  9.8  Political office Holders  77  5.9  Engineer  48  3.6  Religious/traditional leader  24  1.8  Banker  24  1.8  Security officer  35  2.7  Variable.  Frequency.  Percentage.  Age in years       <5  18  1.4  5-19  84  6.4  20-39  666  50.6  40-59  444  33.7  60-79  96  7.3  ≥80  8  0.6  Gender       Male  713  54.2  Female  603  45.8  Location of cases       Rural  147  11.2  Urban  1169  88.8  Type of Education       None  15  1.1  Nursery  8  0.6  Primary  80  6.1  Secondary  204  15.5  Tertiary  1009  76.7  Occupation       Health workers  404  30.7  Businessman and woman  225  17.1  Civil servant  168  12.8  Others  182  13.8  Pupil/Student  129  9.8  Political office Holders  77  5.9  Engineer  48  3.6  Religious/traditional leader  24  1.8  Banker  24  1.8  Security officer  35  2.7  Open in new tab 1170 Table 1: Socio-demographic characteristics of respondents N = 1316 Variable.  Frequency.  Percentage.  Age in years       <5  18  1.4  5-19  84  6.4  20-39  666  50.6  40-59  444  33.7  60-79  96  7.3  ≥80  8  0.6  Gender       Male  713  54.2  Female  603  45.8  Location of cases       Rural  147  11.2  Urban  1169  88.8  Type of Education       None  15  1.1  Nursery  8  0.6  Primary  80  6.1  Secondary  204  15.5  Tertiary  1009  76.7  Occupation       Health workers  404  30.7  Businessman and woman  225  17.1  Civil servant  168  12.8  Others  182  13.8  Pupil/Student  129  9.8  Political office Holders  77  5.9  Engineer  48  3.6  Religious/traditional leader  24  1.8  Banker  24  1.8  Security officer  35  2.7  Variable.  Frequency.  Percentage.  Age in years       <5  18  1.4  5-19  84  6.4  20-39  666  50.6  40-59  444  33.7  60-79  96  7.3  ≥80  8  0.6  Gender       Male  713  54.2  Female  603  45.8  Location of cases       Rural  147  11.2  Urban  1169  88.8  Type of Education       None  15  1.1  Nursery  8  0.6  Primary  80  6.1  Secondary  204  15.5  Tertiary  1009  76.7  Occupation       Health workers  404  30.7  Businessman and woman  225  17.1  Civil servant  168  12.8  Others  182  13.8  Pupil/Student  129  9.8  Political office Holders  77  5.9  Engineer  48  3.6  Religious/traditional leader  24  1.8  Banker  24  1.8  Security officer  35  2.7  Open in new tab Admission and clinical conditions of confirmed cases From Table 2 , 88 (6.7%) of the confirmed cases were admitted as inpatient during investigation, while 325 (24.7%) were symptomatic. The first symptom reported by cases were as follows; cough (98; 30.2%), fever (74; 22.8%), headache (30; 9.2%), runny nose (39; 12.0%), sore throat (24; 7.4%) and difficulty in breathing (15; 4.6%). 1170 Table 2: Admission and clinical conditions of confirmed cases.  Frequency.  Percentage.  Admitted as inpatient before lab testing   Yes  88  6.7  No  1228  93.3  Symptomatic       Yes  325  24.7  No  991  75.3  First symptom reported by respondents (n = 325)   Cough  98  30.2  Fever  74  22.8  Headache  30  9.2  Runny nose  39  12.0  Sore throat/pharyngitis  24  7.4  Difficulty breathing  15  4.6  New loss of taste  9  2.7  New loss of smell  8  2.5  Chest pain  7  2.2  General Body weakness  6  1.8  Others  15  4.6  Outcome       Alive  1287  97.8  Dead  29  2.2 .  Frequency.  Percentage.  Admitted as inpatient before lab testing   Yes  88  6.7  No  1228  93.3  Symptomatic       Yes  325  24.7  No  991  75.3  First symptom reported by respondents (n = 325)   Cough  98  30.2  Fever  74  22.8  Headache  30  9.2  Runny nose  39  12.0  Sore throat/pharyngitis  24  7.4  Difficulty breathing  15  4.6  New loss of taste  9  2.7  New loss of smell  8  2.5  Chest pain  7  2.2  General Body weakness  6  1.8  Others  15  4.6  Outcome       Alive  1287  97.8  Dead  29  2.2  Others= abdominal pain; chills/sweats; joint pain; inability to walk; Nausea Open in new tab 1170 Table 2: Admission and clinical conditions of confirmed cases.  Frequency.  Percentage.  Admitted as inpatient before lab testing   Yes  88  6.7  No  1228  93.3  Symptomatic       Yes  325  24.7  No  991  75.3  First symptom reported by respondents (n = 325)   Cough  98  30.2  Fever  74  22.8  Headache  30  9.2  Runny nose  39  12.0  Sore throat/pharyngitis  24  7.4  Difficulty breathing  15  4.6  New loss of taste  9  2.7  New loss of smell  8  2.5  Chest pain  7  2.2  General Body weakness  6  1.8  Others  15  4.6  Outcome       Alive  1287  97.8  Dead  29  2.2 .  Frequency.  Percentage.  Admitted as inpatient before lab testing   Yes  88  6.7  No  1228  93.3  Symptomatic       Yes  325  24.7  No  991  75.3  First symptom reported by respondents (n = 325)   Cough  98  30.2  Fever  74  22.8  Headache  30  9.2  Runny nose  39  12.0  Sore throat/pharyngitis  24  7.4  Difficulty breathing  15  4.6  New loss of taste  9  2.7  New loss of smell  8  2.5  Chest pain  7  2.2  General Body weakness  6  1.8  Others  15  4.6  Outcome       Alive  1287  97.8  Dead  29  2.2  Others= abdominal pain; chills/sweats; joint pain; inability to walk; Nausea Open in new tab Figure 2 described the epidemic curve of the outbreak from March to August 2020. The index case was confirmed on April 4, 2020. Thereafter, there was a surge in the number of confirmed COVID-19 cases with the outbreak reaching its peak on July 2, 2020. Afterwards, fluctuations in the number of cases were observed before a steady decline was recorded between August 3, 2020 and August 9, 2020. 1170 Figure 2 Open in new tab Download slide Epi-Curve of confirmed cases of COVID-19 in Ondo State, March to August 2020 1170 Figure 2 Open in new tab Download slide Epi-Curve of confirmed cases of COVID-19 in Ondo State, March to August 2020 Association between socio-demographic characteristics, clinical conditions and outcomes of cases In Table 3 , significant proportion of death occurred among cases within the age group 60 years and above (14; 13.5%) compared to other age groups (p < 0.001). Death occurred more among males (26; 3.6%) compared to the females (3; 0.5%) (p < 0.001). Furthermore, symptomatic cases had higher proportion (27; 8.3%) of deaths compared to asymptomatic cases (2; 0.2%) (P < 0.001). Among the symptomatic cases, a high proportion of death was found among those with difficulty in breathing (3; 20%), fever (11; 14.9%), new loss of taste (1; 11.1%), cough (9; 9.2%) and sore throat (2; 8.3%) (P < 0.001) 1170 Table 3: Association between socio-demographic characteristics and outcomes of cases Variable.  Outcome. .  Total.  P-value.  Dead.  Alive.  Age in years           <5  0 (0.0)  18 (100.0)  18  <0.001  5-19  0 (0.0)  84 (100.0)  84    20-39  2 (0.3)  664 (99.7)  666    40-59  13 (2.9)  431 (97.1)  444    ≥60  14 (13.5)  90 (86.5)  104    Gender           Male  26 (3.6)  687 (96.4)  713  <0.001  Female  3 (0.5)  600 (99.5)  603    Location of cases           Rural  5 (3.4)  142 (96.6)  147  0.294  Urban  24 (2.1)  1145 (97.9)  1169    Type of Education           None  1 (6.7)  14 (93.3)  15  0.630  Nursery  0 (0.0)  8 (100.0)  8    Primary  3 (3.8)  77 (96.2)  80    Secondary  4 (2.0)  200 (98.0)  204    Tertiary  21 (2.1)  988 (97.9)  1009    Occupation           Health workers  2 (0.5)  402 (99.5)  24    Businessman and woman  14 (6.2)  211 (93.8)  225    Civil servant  1 (0.6)  167 (99.4)  168  <0.001  Others  10 (5.5)  172 (94.5)  182    Pupil/Student  0 (0.0)  129 (100.0)  129    Politician  0 (0.0)  77 (100.0)  77    Engineer  0 (0.0)  48 (100.0)  48    Religious/traditional ruler  2 (8.3)  22 (91.7)  24    Banker  0 (0.0)  24 (100.0)  24    Security officer  0 (0.0)  35 (100.0)  35    Symptomatic           Yes  27 (8.3)  298 (91.7)  325  <0.001  No  2 (0.2)  989 (99.8)  991    First symptom       N = 325    Cough  9 (9.2)  89 (90.8)  98    Fever  11 (14.9)  63 (85.1)  74  <0.001  Headache  1 (3.3)  29 (96.7)  30    Running nose  0 (0.0)  39 (100.0)  39    Sore throat  2 (8.3)  22 (91.7)  24    New loss of taste  1 (11.1)  8 (88.9)  9    Difficulty in breathing  3 (20.0)  12 (80.0)  15    New loss of smell  0 (0.0)  5 (100.0)  5    Others  0 (0.0)  31 (100.0)  31    Variable.  Outcome. .  Total.  P-value.  Dead.  Alive.  Age in years           <5  0 (0.0)  18 (100.0)  18  <0.001  5-19  0 (0.0)  84 (100.0)  84    20-39  2 (0.3)  664 (99.7)  666    40-59  13 (2.9)  431 (97.1)  444    ≥60  14 (13.5)  90 (86.5)  104    Gender           Male  26 (3.6)  687 (96.4)  713  <0.001  Female  3 (0.5)  600 (99.5)  603    Location of cases           Rural  5 (3.4)  142 (96.6)  147  0.294  Urban  24 (2.1)  1145 (97.9)  1169    Type of Education           None  1 (6.7)  14 (93.3)  15  0.630  Nursery  0 (0.0)  8 (100.0)  8    Primary  3 (3.8)  77 (96.2)  80    Secondary  4 (2.0)  200 (98.0)  204    Tertiary  21 (2.1)  988 (97.9)  1009    Occupation           Health workers  2 (0.5)  402 (99.5)  24    Businessman and woman  14 (6.2)  211 (93.8)  225    Civil servant  1 (0.6)  167 (99.4)  168  <0.001  Others  10 (5.5)  172 (94.5)  182    Pupil/Student  0 (0.0)  129 (100.0)  129    Politician  0 (0.0)  77 (100.0)  77    Engineer  0 (0.0)  48 (100.0)  48    Religious/traditional ruler  2 (8.3)  22 (91.7)  24    Banker  0 (0.0)  24 (100.0)  24    Security officer  0 (0.0)  35 (100.0)  35    Symptomatic           Yes  27 (8.3)  298 (91.7)  325  <0.001  No  2 (0.2)  989 (99.8)  991    First symptom       N = 325    Cough  9 (9.2)  89 (90.8)  98    Fever  11 (14.9)  63 (85.1)  74  <0.001  Headache  1 (3.3)  29 (96.7)  30    Running nose  0 (0.0)  39 (100.0)  39    Sore throat  2 (8.3)  22 (91.7)  24    New loss of taste  1 (11.1)  8 (88.9)  9    Difficulty in breathing  3 (20.0)  12 (80.0)  15    New loss of smell  0 (0.0)  5 (100.0)  5    Others  0 (0.0)  31 (100.0)  31    Others = chest pain, diarrhea, fatigue, joint pain, malaise, nausea, vomiting Open in new tab 1170 Table 3: Association between socio-demographic characteristics and outcomes of cases Variable.  Outcome. .  Total.  P-value.  Dead.  Alive.  Age in years           <5  0 (0.0)  18 (100.0)  18  <0.001  5-19  0 (0.0)  84 (100.0)  84    20-39  2 (0.3)  664 (99.7)  666    40-59  13 (2.9)  431 (97.1)  444    ≥60  14 (13.5)  90 (86.5)  104    Gender           Male  26 (3.6)  687 (96.4)  713  <0.001  Female  3 (0.5)  600 (99.5)  603    Location of cases           Rural  5 (3.4)  142 (96.6)  147  0.294  Urban  24 (2.1)  1145 (97.9)  1169    Type of Education           None  1 (6.7)  14 (93.3)  15  0.630  Nursery  0 (0.0)  8 (100.0)  8    Primary  3 (3.8)  77 (96.2)  80    Secondary  4 (2.0)  200 (98.0)  204    Tertiary  21 (2.1)  988 (97.9)  1009    Occupation           Health workers  2 (0.5)  402 (99.5)  24    Businessman and woman  14 (6.2)  211 (93.8)  225    Civil servant  1 (0.6)  167 (99.4)  168  <0.001  Others  10 (5.5)  172 (94.5)  182    Pupil/Student  0 (0.0)  129 (100.0)  129    Politician  0 (0.0)  77 (100.0)  77    Engineer  0 (0.0)  48 (100.0)  48    Religious/traditional ruler  2 (8.3)  22 (91.7)  24    Banker  0 (0.0)  24 (100.0)  24    Security officer  0 (0.0)  35 (100.0)  35    Symptomatic           Yes  27 (8.3)  298 (91.7)  325  <0.001  No  2 (0.2)  989 (99.8)  991    First symptom       N = 325    Cough  9 (9.2)  89 (90.8)  98    Fever  11 (14.9)  63 (85.1)  74  <0.001  Headache  1 (3.3)  29 (96.7)  30    Running nose  0 (0.0)  39 (100.0)  39    Sore throat  2 (8.3)  22 (91.7)  24    New loss of taste  1 (11.1)  8 (88.9)  9    Difficulty in breathing  3 (20.0)  12 (80.0)  15    New loss of smell  0 (0.0)  5 (100.0)  5    Others  0 (0.0)  31 (100.0)  31    Variable.  Outcome. .  Total.  P-value.  Dead.  Alive.  Age in years           <5  0 (0.0)  18 (100.0)  18  <0.001  5-19  0 (0.0)  84 (100.0)  84    20-39  2 (0.3)  664 (99.7)  666    40-59  13 (2.9)  431 (97.1)  444    ≥60  14 (13.5)  90 (86.5)  104    Gender           Male  26 (3.6)  687 (96.4)  713  <0.001  Female  3 (0.5)  600 (99.5)  603    Location of cases           Rural  5 (3.4)  142 (96.6)  147  0.294  Urban  24 (2.1)  1145 (97.9)  1169    Type of Education           None  1 (6.7)  14 (93.3)  15  0.630  Nursery  0 (0.0)  8 (100.0)  8    Primary  3 (3.8)  77 (96.2)  80    Secondary  4 (2.0)  200 (98.0)  204    Tertiary  21 (2.1)  988 (97.9)  1009    Occupation           Health workers  2 (0.5)  402 (99.5)  24    Businessman and woman  14 (6.2)  211 (93.8)  225    Civil servant  1 (0.6)  167 (99.4)  168  <0.001  Others  10 (5.5)  172 (94.5)  182    Pupil/Student  0 (0.0)  129 (100.0)  129    Politician  0 (0.0)  77 (100.0)  77    Engineer  0 (0.0)  48 (100.0)  48    Religious/traditional ruler  2 (8.3)  22 (91.7)  24    Banker  0 (0.0)  24 (100.0)  24    Security officer  0 (0.0)  35 (100.0)  35    Symptomatic           Yes  27 (8.3)  298 (91.7)  325  <0.001  No  2 (0.2)  989 (99.8)  991    First symptom       N = 325    Cough  9 (9.2)  89 (90.8)  98    Fever  11 (14.9)  63 (85.1)  74  <0.001  Headache  1 (3.3)  29 (96.7)  30    Running nose  0 (0.0)  39 (100.0)  39    Sore throat  2 (8.3)  22 (91.7)  24    New loss of taste  1 (11.1)  8 (88.9)  9    Difficulty in breathing  3 (20.0)  12 (80.0)  15    New loss of smell  0 (0.0)  5 (100.0)  5    Others  0 (0.0)  31 (100.0)  31    Others = chest pain, diarrhea, fatigue, joint pain, malaise, nausea, vomiting Open in new tab Conclusions The outcome of this investigation indicating high transmission among urban residence and health care workers are key public health concerns in the response to the COVID-19 outbreak in Ondo State, Nigeria. Furthermore, high case mortality among the older age groups requires public health intervention. Thus, we recommend intensified risk communication, enhanced surveillance activities, and use of community structures such as community and religious leaders, market and commercial vehicles associations, Ward Development Committee (WDC) and Village Development Committee (VDC) to ensure compliance with public health COVID-19 preventive measures particularly in the urban areas and among those facing a high risk of death. Furthermore, there is a need to prioritize public health interventions including training and vaccination among the vulnerable groups including health care workers who serve as front liners during case investigation, testing and case management. Key messages Enforcement of public health preventive measures particularly in urban settings, and supporting government to strengthen and monitor Infection Prevention and Control practices in hospital settings. [ABSTRACT FROM AUTHOR]

Background While individual countries have gained considerable knowledge and experience in coronavirus disease of 2019 (COVID-19) management, an international, comparative perspective is lacking, particularly regarding the measures taken by different countries to tackle the pandemic. This paper elicits the views of health system staff, tapping into their personal expertise on how the pandemic was initially handled. Methods From May to July 2020, we conducted a cross-sectional, online, purpose-designed survey comprising 70 items. Email lists of contacts provided by the International Society for Quality in Health Care, the Italian Network for Safety in Health Care and the Australian Institute of Health Innovation were used to access healthcare professionals and managers across the world. We snowballed the survey to individuals and groups connected to these organizations. Key outcome measures were attitudes and information about institutional approaches taken; media communication; how acute hospitals were re-organized; primary health organization; personal protective equipment; and staffing and training. Results A total of 1131 survey participants from 97 countries across the World Health Organization (WHO) regions responded to the survey. Responses were from all six WHO regions; 57.9% were female and the majority had 10 or more years of experience in healthcare; almost half (46.5%) were physicians; and all other major clinical professional groups participated. As the pandemic progressed, most countries established an emergency task force, developed communication channels to citizens, organized health services to cope and put in place appropriate measures (e.g. pathways for COVID-19 patients, and testing, screening and tracing procedures). Some countries did this better than others. We found several significant differences between the WHO regions in how they are tackling the pandemic. For instance, while overall most respondents (71.4%) believed that there was an effective plan prior to the outbreak, this was only the case for 31.9% of respondents from the Pan American Health Organization compared with 90.7% of respondents from the South-East Asia Region (SEARO). Issues with swab testing (e.g. delay in communicating the swab outcome) were less frequently reported by respondents from SEARO and the Western Pacific Region compared with other regions. Conclusion The world has progressed in its knowledge and sophistication in tackling the pandemic after early and often substantial obstacles were encountered. Most WHO regions have or are in the process of responding well, although some countries have not yet instituted widespread measures known to support mitigation, for example, effective swab testing and social control measures. [ABSTRACT FROM AUTHOR]

The issue was particularly relevant in the management of the reception centres (RCs) due to the linguistic, cultural and social differences linked to the heterogeneity of the migrants hosted. DepartmentofPublicHealthandInfectiousDiseases,SapienzaUniversityofRome,Vialedel Policlinico155,Rome00161,Italy.Tel:0039-06-49970905;Email:giancarlo.ceccarelli@uniroma1.it Submitted17August2020; Revised3September2020; Accepted10September2020 We read the paper by Greenaway exploring the peculiarities of the coronavirus disease (COVID-19) management in migrant communities. [Extracted from the article]