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Chemosensory scientists have been skeptical that reports of COVID-19 taste loss are genuine, in part because before COVID-19 taste loss was rare and often confused with smell loss. Therefore, to establish the predicted prevalence rate of taste loss in COVID-19 patients, we conducted a systematic review and meta-analysis of 376 papers published in 2020–2021, with 235 meeting all inclusion criteria. Drawing on previous studies and guided by early meta-analyses, we explored how methodological differences (direct vs. self-report measures) may affect these estimates. We hypothesized that direct measures of taste are at least as sensitive as those obtained by self-report and that the preponderance of evidence confirms taste loss is a symptom of COVID-19. The meta-analysis showed that, among 138,015 COVID-19-positive patients, 36.62% reported taste dysfunction (95% confidence interval: 33.02%–40.39%), and the prevalence estimates were slightly but not significantly higher from studies using direct (n = 15) versus self-report (n = 220) methodologies (Q = 1.73, df = 1, P = 0.1889). Generally, males reported lower rates of taste loss than did females, and taste loss was highest among middle-aged adults. Thus, taste loss is likely a bona fide symptom of COVID-19, meriting further research into the most appropriate direct methods to measure it and its underlying mechanisms. [ABSTRACT FROM AUTHOR]

Chemosensory scientists have been skeptical that reports of COVID-19 taste loss are genuine, in part because before COVID-19 taste loss was rare and often confused with smell loss. Therefore, to establish the predicted prevalence rate of taste loss in COVID-19 patients, we conducted a systematic review and meta-analysis of 376 papers published in 2020–2021, with 241 meeting all inclusion criteria. Drawing on previous studies and guided by early meta-analyses, we explored how methodological differences (direct vs. self-report measures) may affect these estimates. We hypothesized that direct measures of taste are at least as sensitive as those obtained by self-report and that the preponderance of evidence confirms taste loss is a symptom of COVID-19. The meta-analysis showed that, among 138,897 COVID-19-positive patients, 39.2% reported taste dysfunction (95% confidence interval: 35.34%–43.12%), and the prevalence estimates were slightly but not significantly higher from studies using direct (n = 18) versus self-report (n = 223) methodologies (Q = 0.57, df = 1, P = 0.45). Generally, males reported lower rates of taste loss than did females, and taste loss was highest among middle-aged adults. Thus, taste loss is likely a bona fide symptom of COVID-19, meriting further research into the most appropriate direct methods to measure it and its underlying mechanisms. [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]

Acupuncture is an important part of Chinese medicine that has been widely used in the treatment of inflammatory diseases. During the coronavirus disease 2019 (COVID-19) epidemic, acupuncture has been used as a complementary treatment for COVID-19 in China. However, the underlying mechanism of acupuncture treatment of COVID-19 remains unclear. Based on bioinformatics/topology, this paper systematically revealed the multi-target mechanisms of acupuncture therapy for COVID-19 through text mining, bioinformatics, network topology, etc. Two active compounds produced after acupuncture and 180 protein targets were identified. A total of 522 Gene Ontology terms related to acupuncture for COVID-19 were identified, and 61 pathways were screened based on the Kyoto Encyclopedia of Genes and Genomes. Our findings suggested that acupuncture treatment of COVID-19 was associated with suppression of inflammatory stress, improving immunity and regulating nervous system function, including activation of neuroactive ligand–receptor interaction, calcium signaling pathway, cancer pathway, viral carcinogenesis, Staphylococcus aureus infection, etc. The study also found that acupuncture may have additional benefits for COVID-19 patients with cancer, cardiovascular disease and obesity. Our study revealed for the first time the multiple synergistic mechanisms of acupuncture on COVID-19. Acupuncture may play an active role in the treatment of COVID-19 and deserves further promotion and application. These results may help to solve this pressing problem currently facing the world. [ABSTRACT FROM AUTHOR]

I noticed a recently published paper named 'Is acupuncture effective in the treatment of COVID-19 related symptoms? Based on bioinformatics/network topology strategy' with great interest. I am inspired and also have some doubts, which are mainly about the active compounds of acupuncture treating COVID-19. The authors choose only two active compounds, which remains to be elucidated clearly with some criteria description. The 11 300 disease targets of COVID-19 were screened using the terms like the related symptoms, which might be other diseases' manifestations. So the better legends of Figures and Tables should be the terms like COVID-19-related symptoms, instead of COVID-19. [ABSTRACT FROM AUTHOR]