Review data from all countries for internal purposes. NOT FOR CIRCULATION.

(last updated: 2021-10-25 07:37:55)

• This reviews latest indicator estimate data in each country (ie., purple tab) - as is.
  
• THREE Stata data files are created by Chelsea and saved in the sharepoint: “/BANICA, Sorin - HSA unit/3 Country implementation & learning/1 HFAs for COVID-19/HFA database/Renamed data/”
  – c19_all.dta
  – cehs_all.dta
  – community_all.dta
  
• This analysis uses the Stata data files (changed from CSV files created in R, as of 8/31/2021), and analysis code is saved in the sharepoint: : “/BANICA, Sorin - HSA unit/3 Country implementation & learning/1 HFAs for COVID-19/HFA database/”
  
• See 1.1 for the date of purple tab production in each survey
  
• See below for date of the pulled dataset creation [FOR NOW DOWNLOAD DATE UNTIL SYNCING PROBLEM IS RESOLVED]

### C19CM
file.mtime(paste0(path,"c19_all.dta"))

[1] “2021-10-24 21:50:00 EST”

### CEHS
file.mtime(paste0(path,"cehs_all.dta"))

[1] “2021-10-24 21:50:00 EST”

### COMMUNITY 
file.mtime(paste0(path,"community_all.dta"))

[1] “2021-10-24 21:50:00 EST”

1. Implementation results

1.1 Overall

See the number of facilities/respondent in each country. Determine what dis-aggregation is possible or not.

Disaggregation by region/county has been excluded (for CMR and KEN).

NOTE: Latest file names manually updated on 9/22/2021, according to Chelsea’s Stata “rename” do files in the shrepoint

1.1.3. COMMUNITY

Community: available data by country

Country	Round	Year	Month	Number of sentinel facilities	Date of latest update for chartbook’s purple tab	File name
Cameroon	1	2021	4	34	2Jun2021	CMR_Community_Chartbook30July2021.xlsx
GHANA	1	2021	6	216	23Aug2021	GH_Community_Chartbook.xlsx
Kenya	1	2020	12	51		summary_Community_Kenya_R1.dta

1.2 Disaggregated

See the number of facilities/respondent in each country. Determine what disaggregation is possible or not.

Disaggregation by region/county has been excluded (for CMR and KEN).

1.2.3. COMMUNITY

Community: available data by country and analysis domain

Country	Round	Year	Round	Analysis.domain	Domain.categories	Number of key informants
Cameroon	1	2021	4	2.Occupation	2.1 ASCs	18
Cameroon	1	2021	4	2.Occupation	2.2 non ASCs	16
GHANA	1	2021	6	Location	1.1 Rural	58
GHANA	1	2021	6	Location	1.2 Urban	158
GHANA	1	2021	6	Role	2.1 non CHVs	88
GHANA	1	2021	6	Role	2.2 CHVs	128
Kenya	1	2020	12	Location	1.1 Rural	25
Kenya	1	2020	12	Location	1.2 Urban	26
Kenya	1	2020	12	Occupation	2.1 non CHWs	4
Kenya	1	2020	12	Occupation	2.2 CHWs	47

3. Results interpretation (FOR GROUP DISCUSSION)

3.3. COMMUNITY

COMMUNITY: Attitude towards COVID-19 vaccine

Percent of communities where most/some people are concerned about COVID-19 and where most people would receive COVID-19 vaccine

• low willingness for vaccine in CMR consistent with low level of concern

COMMUNITY: Reasons for vaccine hesitancy

no concern
1. Not concerned about getting infected with COVID-19

concerns about covid vaccine
2. Uncertain if the COVID-19 vaccine will be effective
3. Concerned about side-effects of the COVID-19 vaccine

concerns about exposure
4. Do not want to go to facilities for fear of getting infected with COVID-19

concerns about vaccine
5. General mistrust of or opposition to any vaccine

time
6. Too busy to get vaccinated

const
7. Concerned about cost

• Francophone Western Africa has more vaccine hesitancy in general even before the pandemic. But, general hesitancy in CMR is not substantially higher than that in KEN & GHA. Why?
  
• Because, in CMR, these reasons are practically answered by all CHWs (about their communities - which is practically general population).
  
• Whereas in KEN & GHA, these reasons are for about half of the CHWs who think not most people in their community would get the COVID vaccine - i.e., select communities. So, general vaccine hesitancy in those settings may appear higher than general vaccine hesitancy in CMR. Still rather puzzling…
  

Note, programmatic: the difference between COVID-19 vaccine specific concerns and general concerns about vaccine suggests potential target groups and interventions.

COMMUNITY: Unmet need

Missing data in Kenya - why??

Unmet need distribution among people who have specific condition/need (Individual)

COMMUNITY: Barriers to access care before the pandemic

COMMUNITY: Barriers to access care since the pandemic

• xbar: moderately or strongly affected access during the pandemic

Q3.2: “During the COVID-19 pandemic, would you say people’s experience in getting health care has generally remained stable, been moderately affected, or been strongly affected? This refers to any type of health services, not only COVID-19 care.”

COMMUNITY: Sources of care, “current”

1. Community health worker
2. Dispensary or health post
3. Hospital
4. Pharmacist or drug/medicine shop
5. COVID testing centre
6. COVID phone line
7. Other trained health care provider
8. Traditional healer
9. Internet or virtual forum
10. Other
11. None (postpone care seeking)

CHW: either the most or one of the most cited source - how much of this is bias? if true, what do the results mean?

COMMUNITY: marginalized groups

• xmargin: any group “disadvantaged in how they access health care for economic, social or cultural reasons”

• unemployed is likely linked to poverty. especially in countries where informal labor is important (e.g., CMR)
  
• this question needs to be more specific, based on answers provided. Also, it worked better in some countries than other.
  
• how is this different from or similar with pre-pandemic patterns?
  

COMMUNITY: Knowledge and risk of COVID-19 infection among key informants

xknowledge: Yes to Q6.1: “Do you feel confident in your knowledge about COVID-19?”
xrisk_mode: moderate OR high
xrisk_high: high

COMMUNITY: Stigma & support

COMMUNITY: Service volume change

COMMUNITY: Community initiatives, health

COMMUNITY: Community initiatives, social/economic