Table 2.
Global learner characteristics.
| Characteristic | Overall (N=2185), n (%) | LMICsa (N=384), n (%) | ||||
| Country group |
|
|
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|
|
High income | 1631 (74.7) | N/Ab | |||
|
|
Upper-middle income | 165 (7.6) | N/A | |||
|
|
Lower-middle income | 266 (12.2) | N/A | |||
|
|
Low income | 118 (5.4) | N/A | |||
|
|
Not specified | 5 (0.2) | N/A | |||
| Region |
|
|
||||
|
|
North America | 1551 (71.0) | 22 (5.7) | |||
|
|
Sub-Saharan Africa | 315 (14.4) | 237 (61.7) | |||
|
|
Europe & Central Asia | 75 (3.4) | 4 (1.0) | |||
|
|
South Asia | 75 (3.4) | 75 (19.5) | |||
|
|
Latin America & Caribbean | 67 (3.0) | 9 (2.3) | |||
|
|
East Asia & Pacific | 56 (2.6) | 37 (9.6) | |||
|
|
Middle East & North Africa | 41 (1.9) | 22 (5.7) | |||
|
|
Not specified | 5 (0.2) | 0 (0.0) | |||
| Preferred language |
|
|
||||
|
|
English | 1664 (76.2) | 298 (77.6) | |||
|
|
Another languagec | 83 (3.8) | 30 (7.8) | |||
|
|
Not specified | 483 (20.0) | 56 (14.6) | |||
| Gender |
|
|
||||
|
|
Female | 1531 (70.1) | 154 (40.1) | |||
|
|
Male | 505 (23.1) | 213 (55.5) | |||
|
|
Nonbinary | 13 (0.6) | 3 (0.8) | |||
|
|
Not specified | 136 (6.2) | 14 (3.7) | |||
| Institutional affiliation |
|
|
||||
|
|
Academic/research institution | 686 (31.4) | 54 (14.1) | |||
|
|
Government | 316 (14.5) | 48 (12.5) | |||
|
|
Hospital, health facility, or clinic | 331 (15.2) | 31 (8.1) | |||
|
|
Intergovernmental/donor agency | 55 (2.5) | 22 (5.7) | |||
|
|
Nongovernmental organization/civil society | 535 (24.5) | 192 (50.0) | |||
|
|
Private sector | 107 (4.9) | 11 (2.9) | |||
|
|
Self-employed/not employed | 155 (7.1) | 26 (6.8) | |||
| Profession |
|
|
||||
|
|
Educator | 61 (2.8) | 15 (3.9) | |||
|
|
Frontline health worker |
|
|
|||
|
|
|
Clinical officer | 23 (1.0) | 10 (2.6) | ||
|
|
|
Community-based health worker | 379 (17.4) | 34 (8.9) | ||
|
|
|
Doctor | 92 (4.2) | 45 (11.7) | ||
|
|
|
Nurse midwife | 268 (12.3) | 21 (5.5) | ||
|
|
Government official | 37 (1.7) | 8 (2.1) | |||
|
|
Health educator | 78 (3.6) | 13 (3.4) | |||
|
|
Health worker trainer/supervisor | 84 (3.8) | 23 (6.0) | |||
|
|
Program manager | 222 (10.2) | 87 (22.7) | |||
|
|
Student | 558 (25.5) | 19 (5.0) | |||
|
|
Technical assistance provider | 114 (5.2) | 45 (11.7) | |||
|
|
Other health professionald | 90 (4.1) | 21 (5.5) | |||
|
|
Other professionale | 222 (10.2) | 43 (11.2) | |||
| COVID-19 response involvementf |
|
|
||||
|
|
Contact tracing | 485 (22.2) | 79 (20.6) | |||
|
|
Risk communication and community engagement | 893 (40.9) | 278 (72.4) | |||
|
|
Surveillance | 303 (13.9) | 111 (28.9) | |||
|
|
Testing | 169 (7.8) | 36 (9.4) | |||
|
|
Treatment | 333 (15.3) | 48 (12.5) | |||
|
|
Other | 511 (23.4) | 123 (32.0) | |||
|
|
None | 639 (29.2) | 40 (10.4) | |||
aLMICs: low- and middle-income countries.
bN/A: not applicable.
cOther languages preferred (in order of the highest to lowest demand) were Spanish, French, Portuguese, Arabic, Hindi, Bengali, Burmese, Indonesian, Russian, German, Italian, Swahili, Ukrainian, Khmer, Krio, and Telugu.
dOther health professionals included dentists, environmental health and safety professionals, epidemiologists, medical assistants, nutritionists, pharmacists, psychologists, social workers, and case managers.
eOther professionals included human resource professionals, librarians, media specialists, researchers, translators, and other unspecified professions.
fEnrollees could select multiple types of COVID-19 response involvements, and hence, percentages do not add to 100.