(last updated: 2021-10-19 07:03:38)
### C19CM
file.mtime(paste0(path,"c19_all.dta"))[1] “2021-10-19 10:59:00 EST”
### CEHS
file.mtime(paste0(path,"cehs_all.dta"))[1] “2021-10-19 10:59:00 EST”
### COMMUNITY
file.mtime(paste0(path,"community_all.dta"))[1] “2021-10-19 10:59:00 EST”
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
| Country | Round | Year | Month | Number of sentinel facilities | Date of latest update for chartbook’s purple tab | File name |
|---|---|---|---|---|---|---|
| Cameroon | 1 | 2021 | 4 | 60 | 21Jul2021 | CMR_WHO_COVID19HospitalReadiness_Chartbook_30July2021.xlsx |
| Ghana | 1 | 2021 | 6 | 35 | 23Aug2021 | Ghana_COVID19HospitalReadiness_Chartbook.xlsx |
| Kenya | 1 | 2020 | 12 | 74 | summary_COVID19HospitalReadiness_Kenya_R1.dta | |
| Kenya | 2 | 2021 | 4 | 77 | KEN_Hospital_Chartbook_R2_26_05_2021_JK_(Jamlick).xlsx | |
| Namibia | 1 | 2021 | 8 | 43 | 15Sep2021 | Namibia_COVID19HospitalReadiness_Chartbook_ADAPTED219.xlsx |
| Zambia | 1 | 2021 | 7 | 53 | 19Aug2021 | Zambia_WHO_COVID19HospitalReadiness_Chartbook_20082021.xlsx |
| Country | Round | Year | Month | Number of sentinel facilities | Date of latest update for chartbook’s purple tab | File name |
|---|---|---|---|---|---|---|
| Cameroon | 1 | 2021 | 4 | 186 | 19Jul2021 | CMR_CEHS_Chartbook_30July2021.xlsx |
| Ghana | 1 | 2021 | 6 | 143 | 23Aug2021 | Ghana_CEHS_Chartbook.xlsx |
| Kenya | 1 | 2020 | 12 | 91 | summary_CEHS_Kenya_R1.dta | |
| Kenya | 2 | 2021 | 4 | 106 | KEN_CEHS_Chartbook_R2_JK_01062021 (Jamlick).xlsx | |
| Namibia | 1 | 2021 | 8 | 116 | 21Sep2021 | Namibia_CEHS_chartbook_ADAPTED-16_db.xlsx |
| Ukraine | 1 | 2021 | 4 | 250 | WHO_CEHS_chartbook_UKRAINE_v7_with_updated_navy_tab.xlsx | |
| Zambia | 1 | 2021 | 7 | 242 | 18Aug2021 | WHO_CEHS_Zambia_Chartbook_Final_20082021.xlsx |
| 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 |
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).
| Country | Round | Year | Round | Analysis.domain | Domain.categories | Number of sentinel facilities |
|---|---|---|---|---|---|---|
| Cameroon | 1 | 2021 | 4 | Sector | Non-public | 4 |
| Cameroon | 1 | 2021 | 4 | Sector | Public | 56 |
| Ghana | 1 | 2021 | 6 | Level | District Hospital | 27 |
| Ghana | 1 | 2021 | 6 | Level | Regional Hospital | 8 |
| Ghana | 1 | 2021 | 6 | Location | Rural | 7 |
| Ghana | 1 | 2021 | 6 | Location | Urban | 28 |
| Ghana | 1 | 2021 | 6 | Sector | Government | 26 |
| Ghana | 1 | 2021 | 6 | Sector | Non-Government | 9 |
| Kenya | 1 | 2020 | 12 | Level | Level 2-4 | 47 |
| Kenya | 1 | 2020 | 12 | Level | Level 5-6 | 27 |
| Kenya | 1 | 2020 | 12 | Location | Rural | 28 |
| Kenya | 1 | 2020 | 12 | Location | Urban | 46 |
| Kenya | 1 | 2020 | 12 | Sector | Non-public | 16 |
| Kenya | 1 | 2020 | 12 | Sector | Public | 58 |
| Kenya | 2 | 2021 | 4 | Level | Level 4 | 58 |
| Kenya | 2 | 2021 | 4 | Level | Level 5 | 15 |
| Kenya | 2 | 2021 | 4 | Level | Level 6 | 4 |
| Kenya | 2 | 2021 | 4 | Location | Rural | 30 |
| Kenya | 2 | 2021 | 4 | Location | Urban | 47 |
| Kenya | 2 | 2021 | 4 | Sector | Non-public | 15 |
| Kenya | 2 | 2021 | 4 | Sector | Public | 62 |
| Namibia | 1 | 2021 | 8 | Level | Primary/Secondary | 7 |
| Namibia | 1 | 2021 | 8 | Level | Tertiary | 36 |
| Namibia | 1 | 2021 | 8 | Location | Rural | 6 |
| Namibia | 1 | 2021 | 8 | Location | Urban | 37 |
| Namibia | 1 | 2021 | 8 | Sector | Non-public | 12 |
| Namibia | 1 | 2021 | 8 | Sector | Public | 31 |
| Zambia | 1 | 2021 | 7 | Level | Primary/Secondary | 2 |
| Zambia | 1 | 2021 | 7 | Level | Tertiary | 51 |
| Zambia | 1 | 2021 | 7 | Location | Rural | 15 |
| Zambia | 1 | 2021 | 7 | Location | Urban | 38 |
| Zambia | 1 | 2021 | 7 | Sector | Non-public | 17 |
| Zambia | 1 | 2021 | 7 | Sector | Public | 36 |
| Country | Round | Year | Round | Analysis.domain | Domain.categories | Number of sentinel facilities |
|---|---|---|---|---|---|---|
| Cameroon | 1 | 2021 | 4 | Sector | 3.1 Publique | 100 |
| Cameroon | 1 | 2021 | 4 | Sector | 3.2 Privé laic | 58 |
| Cameroon | 1 | 2021 | 4 | Sector | 3.3 Privé confessionnel | 27 |
| Ghana | 1 | 2021 | 6 | Level | CHPS/Clinic/Health Centre | 108 |
| Ghana | 1 | 2021 | 6 | Level | Hospitals | 35 |
| Ghana | 1 | 2021 | 6 | Location | Rural | 80 |
| Ghana | 1 | 2021 | 6 | Location | Urban | 63 |
| Ghana | 1 | 2021 | 6 | Sector | Government | 123 |
| Ghana | 1 | 2021 | 6 | Sector | Non-Government | 20 |
| Kenya | 1 | 2020 | 12 | Level | Level 2-3 | 44 |
| Kenya | 1 | 2020 | 12 | Level | Level 4-6 | 47 |
| Kenya | 1 | 2020 | 12 | Location | Rural | 58 |
| Kenya | 1 | 2020 | 12 | Location | Urban | 33 |
| Kenya | 1 | 2020 | 12 | Sector | Non-public | 24 |
| Kenya | 1 | 2020 | 12 | Sector | Public | 67 |
| Kenya | 2 | 2021 | 4 | Level | Level 2-3 | 48 |
| Kenya | 2 | 2021 | 4 | Level | Level 4 | 58 |
| Kenya | 2 | 2021 | 4 | Location | Rural | 68 |
| Kenya | 2 | 2021 | 4 | Location | Urban | 38 |
| Kenya | 2 | 2021 | 4 | Sector | Non-public | 24 |
| Kenya | 2 | 2021 | 4 | Sector | Public | 82 |
| Namibia | 1 | 2021 | 8 | Level | Primary | 106 |
| Namibia | 1 | 2021 | 8 | Level | Secondary | 10 |
| Namibia | 1 | 2021 | 8 | Location | Rural | 63 |
| Namibia | 1 | 2021 | 8 | Location | Urban | 53 |
| Namibia | 1 | 2021 | 8 | Sector | Non-public | 19 |
| Namibia | 1 | 2021 | 8 | Sector | Public | 97 |
| Ukraine | 1 | 2021 | 4 | Level | Hospitals | 36 |
| Ukraine | 1 | 2021 | 4 | Level | Primary | 214 |
| Ukraine | 1 | 2021 | 4 | Location | Rural | 17 |
| Ukraine | 1 | 2021 | 4 | Location | Urban | 233 |
| Ukraine | 1 | 2021 | 4 | Sector | Non-public | 25 |
| Ukraine | 1 | 2021 | 4 | Sector | Public | 225 |
| Zambia | 1 | 2021 | 7 | Level | Primary | 212 |
| Zambia | 1 | 2021 | 7 | Level | Secondary | 30 |
| Zambia | 1 | 2021 | 7 | Location | Rural | 104 |
| Zambia | 1 | 2021 | 7 | Location | Urban | 138 |
| Zambia | 1 | 2021 | 7 | Sector | Non-public | 29 |
| Zambia | 1 | 2021 | 7 | Sector | Public | 213 |
| 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 |
| 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 |
A. Clear errors (or very odd cases)
A.1. _100 vs. _50
Results: details
A.2. More restrictive vs. less restrictive
* xtraining_score vs. xtrainingsupport_score
* xppe_allsome_score vs. xppe_all_score
* xequip_all vs. zequip_any
| survey | redflag_xtraining |
|---|---|
| GHA_R1 | 1 |
| NAM_R1 | 1 |
A.3. Other
* Data entry for the number of beds
| survey | redflag_bed1 |
|---|---|
| CMR_R1 | 1 |
| KEN_R2 | 1 |
| ZMB_R1 | 4 |
Results: details
B. Likely errors, based on pattern that we observe
* ybed_cap_isolation vs. ybed_cap_covid_severe/critical
* clinical staff infections vs. non-clinical staff infection
| survey | redflag_bed1 | redflag_staffcovid1 |
|---|---|---|
| CMR_R1 | 1 | 0 |
| GHA_R1 | 0 | 2 |
| KEN_R2 | 1 | 1 |
| NAM_R1 | 0 | 2 |
| ZMB_R1 | 6 | 1 |
Results: details
A. Clear errors (or very odd cases)
A.1. _100 vs. _50
A.2. More restrictive vs. less restrictive
* xtraining_score vs. xtrainingsupport_score
* xppe_allsome_score vs. xppe_all_score
* xdiagbasic_score vs. xdiag_score
* xcvd_ref vs. xcvd_reftrans
Results: details
B. Likely errors, based on pattern that we observe
data quality comments are in blue box
xspcmitem_score: Average specimen collection items score (range: 0-100), among all facilities
xrdt_capacity: Average current testing load out of maximum capacity (%), Among those that conduct RDT tests onsite
xpcr_capacity: Average current testing load out of maximum capacity (%), among those that conduct PCR tests onsite
xdiagcovid_score: Average COVID diagnosis score (range: 0-100), among all facilities
xdrug_score: Average medicines score (range: 0-100), among all facilities
xsupp_score: Average supplies score (range: 0-100), among all facilities
xequip_anyfunction_score: Average equipment score, any quantity functioning (range: 0-100), among all facilities
xequip_allfunction_score: Average equipment score, all quantity functioning (range: 0-100), among all facilities
Note: Do further analysis of “scores” by IMST status. If no difference, consider dropping the questioins.
ybed: Total pooled number of inpatient beds
ybed_cap_covid: Total pooled number of inpatient beds that can be used for any COVID-19 patients
ybed_cap_covid_severe: Total pooled number of inpatient beds that can be used for severe COVID-19 patients (not requiring intensive care)
ybed_cap_covid_critical: Total pooled number of inpatient beds that can be used for critical COVID-19 patients (requiring intensive care)
ybed_cap_noncovid: ybed - ybed_cap_covid
ybed_cap_respiso: Total pooled number of inpatient beds that can be used for respiratory isolation
ybed_covid_night: Total pooled number of inpatient beds currently occupied by confirmed/suspected COVID-19 patients (Average over two days)
ybed_convert_respiso: Total pooled number of inpatient beds that can be converted for respiratory isolation, if needed
ybed_convert_icu: Total pooled number of inpatient beds that can be converted for ICU, if needed
Note: Cameroon: ybed_cap_covid >> ybed_cap_respiso. French Q tanslation issue or health systems difference? “ybed_cap_respiso” is an add/unclear indicator.
A good example that interpretation requires COVID-19 transmission context.
- Kenya R2 & Zambia R1 were conducted in the middle of an outbreak - post-peak, when hospitalizations would have peaked….
- Ghana R1 was done during the low phase, right before an outbreak/peak.
xppe: % of facilities that provide PPE to staff
xppe_allsome_100: % of facilities that have each of all 6 tracer PPE items currently available for all or some staff
xppe_allsome_50: % of facilities that have 50% or more of the tracer items
xppe_all_100: % of facilities that have each of all 6 tracer PPE items currently available for all staff
xppe_all_50: % of facilities that have 50% or more of the tracer items
xppedispose: % of facilities that dispose used PPE safely according to the IPC guidelines
Self reported PPE dispose is universally high - DROP (from round 2)
Note, programmatic: availability of any functioning ventilators (invasive and non-invasive) is sub-optimal. Even if they exist and functional, we do not know if the number of ventilators can address an outbreak.
Note: internally consistent - generally.
But, what is the difference between xoxygen_cylinder vs. xoxygen_portcylinder? The relationship is different in Kenya R2. Data error/different interpretation or actual difference?
oxygen availability is universally good, though distribution is low (no immediate intervention possible for this).
Note, programmatic:
* staff absence is common (expected?), but they are not necessarily for COVID related reasons (as reported by respondents/manager).
* See increase/shift in reasons in Kenya, reflecting burn out as the pandemic prolongs?.
xppe: % of facilities that provide PPE to staff
xppe_allsome_100: % of facilities that have each of all 6 tracer PPE items currently available for all or some staff
xppe_allsome_50: % of facilities that have 50% or more of the tracer items
xppe_all_100: % of facilities that have each of all 6 tracer PPE items currently available for all staff
xppe_all_50: % of facilities that have 50% or more of the tracer items
xppedispose: % of facilities that dispose used PPE safely according to the IPC guidelines
What do we do/act with this data? Does every facility need to have a referral facility??? what does that mean, if/when patient volume surges?
Note: check Kenya R1.
xcvd_pt: % of primary-level facilities that have seen patients with suspected COVID-19 in the past 3 months
xcvd_pt_sep_room: Among primary-level facilities that had COVID-19 patients in the past 3 months, % of primary-level facilities that performed: Patient consultation takes place in a separate room
xcvd_pt_c19_check: Among primary-level facilities that had COVID-19 patients in the past 3 months, % of primary-level facilities that performed: Checked for COVID-19 symptoms
xcvd_pt_o2_measure: Among primary-level facilities that had COVID-19 patients in the past 3 months, % of primary-level facilities that performed: Measured O2 saturation with pulse oximeter
xcvd_pt_refer: Among primary-level facilities that had COVID-19 patients in the past 3 months, % of primary-level facilities that performed: Referred the patient to specialized care
xcvd_pt_diagtest: Among primary-level facilities that had COVID-19 patients in the past 3 months, % of primary-level facilities that performed: Performed diagnostic test
xcvd_pt_home_isolate: Among primary-level facilities that had COVID-19 patients in the past 3 months, % of primary-level facilities that performed: Instructed patients with mild symptoms to self-isolate at home
xcvd_pt_tele: Among primary-level facilities that had COVID-19 patients in the past 3 months, % of primary-level facilities that performed: Provided teleconsultation to answer patient’s questions before facility visit
xcvd_pt_score: Average score for COVID-19 patients management based on the tracer items (range: 0-100), among primary-level facilities that had COVID-19 patients in the past 3 months
xcvd_pt_100: Among primary-level facilities that had COVID-19 patients in the past 3 months, % of facilities that have performed all seven tracer items for management of COVID-19 patients
xcvd_pt_50: Among primary-level facilities that had COVID-19 patients in the past 3 months, % of facilities that have performed 50% of tracer items for management of COVID-19 patients
Note: Ghana should drop these xcvd_pt questions. Too small denominator.
xcvd_pthbsi: % of primary-level facilities that have instructed home isolation for mild COVID-19 patients
xcvd_pthbsi_tele: % of primary-level facilities that have instructed home isolation for mild COVID-19 patients AND: Provided remote consultation (phone or video call, text message)
xcvd_pthbsi_homevisit: % of primary-level facilities that have instructed home isolation for mild COVID-19 patients AND: Visited patients at home
xcvd_pthbsi_followup: % of primary-level facilities that have instructed home isolation for mild COVID-19 patients AND: Arranged follow-up visit to the facility (e.g. by asking the patient to report to a designated entrance at prearranged appointment time)
xcvd_pthbsi_safetyinstruct: % of primary-level facilities that have instructed home isolation for mild COVID-19 patients AND: Provided safety instructions for the members of the patient’s household
xcvd_pthbsi_complianceassess: % of primary-level facilities that have instructed home isolation for mild COVID-19 patients AND: Assessed compliance with self-isolation
xcvd_pthbsi_report: % of primary-level facilities that have instructed home isolation for mild COVID-19 patients AND: Reported the home-based self-isolation and care patients to relevant health authority
xcvd_guide_casemanage: % of primary-level facilities that have received up-to-date guidelines to manage asymptomatic or mild COVID-19 cases, including for referral
Note: Ghana should drop these xcvd_pthbsi questons. Too small denominator.
Note: in CMR, “other” is the major source. What are they?
xcovax: % of facilities that provide COVID-19 vaccine
**xcovax_offer__pfizer**: Among facilities that provide COVID-19 vaccine, % of facilities that offer vaccine 001
**xcovax_offerav__pfizer**: Among facilities that provide COVID-19 vaccine, % of facilities that offer and have vaccine 001
**xcovax_offer__moderna**: Among facilities that provide COVID-19 vaccine, % of facilities that offer vaccine 002
**xcovax_offerav__moderna**: Among facilities that provide COVID-19 vaccine, % of facilities that offer and have vaccine 002
**xcovax_offer__astra**: Among facilities that provide COVID-19 vaccine, % of facilities that offer vaccine 003
**xcovax_offerav__astra**: Among facilities that provide COVID-19 vaccine, % of facilities that offer and have vaccine 003
**xcovax_offer__jj**: Among facilities that provide COVID-19 vaccine, % of facilities that offer vaccine 004
**xcovax_offerav__jj**: Among facilities that provide COVID-19 vaccine, % of facilities that offer and have vaccine 004
See the gap between “offer” vs. “available” in GHA and ZMB.
xcovax_syr: Among facilities that provide COVID-19 vaccine, % of facilities that syringes
xcovax_sharp: Among facilities that provide COVID-19 vaccine, % of facilities that have sharps containers
xcovax_strtemp: Among facilities that provide COVID-19 vaccine, % of facilities that have cold storage for COVID-19 vaccine remaining in the recommended temperature range, currently
xcovax_strtemp_w: Among facilities that provide COVID-19 vaccine, % of facilities that have cold storage for COVID-19 vaccine remaining in the recommended temperature range, currently AND for the past week
xcovax_aefikit: Among facilities that provide COVID-19 vaccine, % of facilities that have AEFI kit
xcovax_aefireport: Among facilities that provide COVID-19 vaccine, % of facilities that have system to report AEFI to the central center
See cold chain issues in GHA.
Missing aefi data - why??
Reported training is universally high. Probably not reporting bias, since the vaccine is brand new.
(Facilities can provide multiple strategies.)
Note: reflection of various context. no benchmark. requires context specific interpretation.
* Makes sense that Ukraine looks different from others. See remote and prescription.
* Very few closure. Mostly reduced hours. Scope reduction is not common. Meaning service availability did not change drastically - especially for priority patients.
xopt_increase: % of facilities that have had increased outpatient attendance in the past 3 months in one or more of the 18 services listed
xopt_increase_reason_covidnow: % of facilities that have had increased outpatient attendance in the past 3 months AND cited reasons reflecting current outbreak
xopt_increase_reason_covidafter: % of facilities that have had increased outpatient attendance in the past 3 months AND cited reasons reflecting impact of past outbreak
xopt_increase_reason_gbv: % of facilities that have had increased outpatient attendance in the past 3 months AND cited reasons reflecting GBV
xopt_decrease: % of facilities that have had decreased outpatient attendance in the past 3 months in one or more of the 18 services listed
xopt_decrease_reason_comdemand: % of facilities that have had decreased outpatient attendance in the past 3 months AND cited reasons reflecting community demand changes
xopt_decrease_reason_enviro: % of facilities that have had decreased outpatient attendance in the past 3 months AND cited reasons reflecting barriers in care seeking
xopt_decrease_reason_intention: % of facilities that have had decreased outpatient attendance in the past 3 months AND cited reasons reflecting changes in service provision strategies
xopt_decrease_reason_disruption: % of facilities that have had decreased outpatient attendance in the past 3 months AND cited reasons reflecting disruption at the facility level
(Facilities can provide multiple reasons.)
xopt_increase and xopt_decrease would be yes in most facilities, unless they are specialized in particular services (which should not be part of the EHS sample anyway, in theory)Similar indicators:
* In section 7, __xdisrupt_supply**: % of facilities that reported service disruption due to supply stock out (potentially leading question)
* In section 4, __xopt_decrease_reason_disruption**: % of facilities that have had decreased outpatient attendance in the past 3 months AND cited reasons reflecting disruption at the facility level
xer: % of facilities providing emergency unit services
xer_increase: Among facilities with emergency unit, % of facilities that have had overall increased emergency unit visits in the past 3 months compared to the same months last year
xer_decrease: Among facilities with emergency unit, % of facilities that have had overall decreased emergency unit visits in the past 3 months compared to the same months last year
xer_nochange: Among facilities with emergency unit, % of facilities that have had overall no changes in emergency unit visits in the past 3 months compared to the same months last year
**xer_increase__002**: Among facilities with emergency unit. % of facilities that have had increased emergency unit visits for injuries in the past 3 months
**xer_increase__003**: Among facilities with emergency unit. % of facilities that have had increased emergency unit visits for emergency surgeries in the past 3 months
**xer_increase__004**: Among facilities with emergency unit. % of facilities that have had increased emergency unit visits for NCD related conditions in the past 3 months
**xer_increase__005**: Among facilities with emergency unit. % of facilities that have had increased emergency unit visits for emergency blood transfusion services in the past 3 months
**xer_decrease__002**: Among facilities with emergency unit. % of facilities that have had decreased emergency unit visits for injuries in the past 3 months
**xer_decrease__003**: Among facilities with emergency unit. % of facilities that have had decreased emergency unit visits for emergency surgeries in the past 3 months
**xer_decrease__004**: Among facilities with emergency unit. % of facilities that have had decreased emergency unit visits for NCD related conditions in the past 3 months
**xer_decrease__005**: Among facilities with emergency unit. % of facilities that have had decreased emergency unit visits for emergency blood transfusion services in the past 3 months
xout: % of facilities that provide community outreach or home-visit services
**xout_decrease__immun**: Among facilities providing community outreach or home-visit services, % of facilities that have reduced or suspended: Immunization outreach
**xout_decrease__malaria**: Among facilities providing community outreach or home-visit services, % of facilities that have reduced or suspended: Malaria prevention campaigns, including distribution of ITN
**xout_decrease__ntd**: Among facilities providing community outreach or home-visit services, % of facilities that have reduced or suspended: Neglected tropical disease outreach activities, including mass drug administration
**xout_decrease__cbc**: Among facilities providing community outreach or home-visit services, % of facilities that have reduced or suspended: Community-based mobile clinics
**xout_decrease__home**: Among facilities providing community outreach or home-visit services, % of facilities that have reduced or suspended: home visits
xout_decrease: Among facilities providing community outreach or home-visit services, % of facilities that have reduced or suspended one or more of the five services (see below) in the past three months
xresto: % of facilities that have developed plans to deliver services for patients who missed their routine appointments that are unrelated with COVID-19 in the previous 3 months AND registered them
xresto_imp_preg: Among facilities that provide ANC, % of facilities that have implemented plans for targeted catch up for pregnant women who missed appointments in the past three months
xresto_imp_immunization: Among facilities that provide child immunization, % of facilities that have implemented plans for targeted catch up for missed appointments for childhood immunization
xresto_imp_chronic: Among facilities that provide NCD, % of facilities that have implemented plans for targeted catch up for chronic non-communicable diseases patients who missed appointments in the past three months
xresto_imp_tb: Among facilities that provide TB, % of facilities that have implemented plans for targeted catch up for TB patients who missed appointments in the past three months
xresto_imp_hiv: Among facilities that provide HIV, % of facilities that have implemented plans for targeted catch up for HIV patients who missed appointments in the past three months
xresto_imppln_preg: Among facilities that provide ANC, % of facilities that have developed or implemented plans for targeted catch up for pregnant women who missed appointments in the past three months
xresto_imppln_immunization: Among facilities that provide child immunization, % of facilities that have developed or implemented plans for targeted catch up for missed appointments for childhood immunization
xresto_imppln_chronic: Among facilities that provide NCD, % of facilities that have developed or implemented plans for targeted catch up for chronic non-communicable diseases patients who missed appointments in the past three months
xresto_imppln_tb: Among facilities that provide TB, % of facilities that have developed or implemented plans for targeted catch up for TB patients who missed appointments in the past three months
xresto_imppln_hiv: Among facilities that provide HIV, % of facilities that have developed or implemented plans for targeted catch up for HIV patients who missed appointments in the past three months
Percent of communities where most/some people are concerned about COVID-19 and where most people would receive COVID-19 vaccine
Note, programmatic: the difference between COVID-19 vaccine specific concerns and general concerns about vaccine suggests potential target groups and interventions.
Missing data - why??
Met/unmet need distribution among people who have specific condition/need (Individual)