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Preparedness of Health Care Systems forPreparedness of Health Care Systems for
Ebola Outbreak in Kasese and RubiriziEbola Outbreak in Kasese and Rubirizi
Districts, Western UgandaDistricts, Western Uganda
Kibuule Michael
Makerere University College of Health Sciences-
school of Public Health
Background and IntroductionBackground and Introduction
 Ebola virus disease constitutes the biggest public health problem
worldwide and has occurred with increased frequency in the
last five years
 First insolated 1976 in Sub Saharan Africa. (W H O, 2014)
 First incidence of EVD in Uganda happened in Gulu district
Aug/2000- to- 01/2001, CFR of 80% (Lamunu, et al., 2004)
 Preparedness is Knowledge and other capacities developed by
individuals, communities, governments, professional response and
recovery organizations (UNISDR, 2009)
 Preparedness level of health care systems determine magnitude and
impact of EVD outbreak (WHO, 2014)
2
Literature ReviewLiterature Review
 Health care system preparedness is optimal when it meets;
 Infrastructural-triage space,
 Rapid response teams,
 EVD committees,
 Isolation units,
 Surveillance systems,
 Case definition,
 Knowledgeable of health workers,
 Plus logistics
 Ebola virus belongs to the Filoviridae family, Species are;
Bundibugyo, Côte d’Ivoire, Reston, Sudan, and Zaire (WHO, 2014
 Incubation period of EVD is 2–21 days, and it presents with early
and late stages
 Known risk factors for EVD outbreak- Behavioral, Cultural, and
institutional, Physical contact and Poor Hand Hygiene
3
Conceptual FrameworkConceptual Framework
4
ObjectivesObjectives
General Objective
To assess preparedness of health care system for Ebola
outbreak response in Kasese and Rubirizi districts
Specific Objectives
To establish preparedness level of District Health Infrastructure to
respond to EVD outbreak
To determine logistical preparedness of health facilities to manage a
suspected incident of Ebola disease case in Kasese and Rubirizi
districts
To establish health care workers’ level of knowledge on
preparedness for containment of Ebola disease outbreak in Kasese
and Rubirizi districts
To determine overall level of preparedness for EVD outbreak and
response in Kasese and Rubirizi districts 6
MethodologyMethodology
Study Site and PopulationStudy Site and Population
Study population/Units
All Hospital level facilities, all H/CIV level facilities, selected
H/CIII facilities in Kasese district.
Doctors, Medical Clinical Officers, Nurses, laboratory technicians,
midwives and Nursing assistants 7
MethodologyMethodology
Study Design and Sampling ProceduresStudy Design and Sampling Procedures
 Cross-sectional study with mixed methods
 All hospitals and H/CIVs in both districts were
purposively selected
 Fifty percent H/CIIIs in each district were randomly
selected using a ballot papers
 List of H/CIIIs was obtained, ballot papers with their
names written, then randomly selected until desired
number was obtained
 Number of HCWs selected using simple random
sampling
8
Data collection toolsData collection tools
Category of
respondents
Data collection instruments Tool
DHTs, DDMCs Key informants KI guide
Departmental heads/In-
charges
FGDs FGD guide
Health care workers Structured questionnaires Questionnaire
Facility In-charges,
hospital Administrators
Facility checklists Checklist
9
Data Management & AnalysisData Management & Analysis
 Data was cleaned and triangulated before entry
 Data entry was done from structured questionnaire
using Epi-data
 Data was then analyzed with STATA (Version.14)
 Level of infrastructure preparedness was measured on a
14-point scale
 All “Yes” responses scored 1 and the “No” responses
score 0
10
Data Analysis cont’Data Analysis cont’
Knowledge, a bivariate analysis was carried out using
2x2 table analysis
Social demographic characteristics as independent
variable
Independent covariates were regressed on level of
knowledge using equation of a straight line in
multivariate logistic regression
Level of knowledge as a dependent variable
Unadjusted and adjusted odds ratio was used to assess
the level of association at 0.05 significance level 13
Analysis cont’Analysis cont’
Qualitative analysis.
Researcher read through transcripts several times
Drew categories and clustered data among themes
Themed the categories as;-“Knowledge”, “logistics”,
“Capacity”
Summarized and displayed quotes
In-depth reading and creating meaning from data was
done
 Researcher then developed conclusions from data
14
Factor Level
Kasese
(n=148)
Rubirizi
(n=39) p-value
N   (% )148 (%)39  
Gender Female 55.4%(82) 56.4%(22) 0.91
  Male 44.6%(66) 43.6%(17)  
Age 20-30 51.0%(75) 58.3%(21) 0.73
  31-40 28.6%(42) 25.0%(9)  
  41 and above 20.4%(30) 16.7%(6)  
Religion Catholic 29.3%(43) 51.3%(20) 0.011
  Muslim 4.1%(6) 2.6%(1)  
  Pentecostal 0.0%(0) 2.6%(1)  
  Pentecostal Baptist 2.7%(4) 0.0%(0)  
  Protestant 54.4%(80) 28.2%(11)  
  Seventh day Adventist 9.5%(14) 15.4%(6)  
Education level Primary level 1.4%(2) 2.6%(1) 0.72
  Secondary level 6.1%(9) 2.6%(1)  
  Tertiary level 83.0%(122) 82.1%(32)  
  University 9.5%(14) 12.8%(5)  
Job designation Senior Medical officer 0.0%(0) 3.2%(1) 0.097
  Medical officer 4.2%(5) 0.0%(0)  
  Senior medical clinical officer 20.2%(24) 12.9%(4)  
  Senior nursing officer 3.4%(4) 3.2%(1)  
  Enrolled registered midwife 37.1%(56) 67.7%(21)  
  lab technologist 16.8%(20) 12.9%(4)  
  other 8.4%(10) 0.0%(0)  
Nature of employment Permanent 50.3%(74) 82.1%(32) <0.001
  Temporary 43.5%(64) 12.8%(5)  
  Volunteer 6.1%(9) 2.6%(1)  
  others 0.0%(0) 2.6%(1)   16
Demographic of Health Care Workers in Kasese and Rubirizi
Districts
BivarianteBivariante
Independent variables
Knowledge level
 
COR(95% CI) P-
value
AOR (95% CI) P-value
Low(n=104)
High (83)      
 
Gender        
Female 61(58.7) 43(51.8)        
Male 43(41.3) 40(48.2) 1.31(0.74-2.36) 0.350 0.88(.043-1.83) 0.747
Age        
20-30 48(48.0) 48(57.0)        
31-40 30(30.0) 21(26.3) 0.7(0.35-1.39) 0.308 0.65(0.28-1.46) 0.295
41 and above 22(22.0) 14(16.9) 0.64(0.29-1.39) 0.256 0.33(0.11-0.91) 0.032*
Education level        
Secondary level 11(10.6) 2(2.4)        
Tertiary level 93(89.4) 80(97.6) 4.73(1.01-21.9) 0.047* 1 -
Job designation        
Clinician 16(21.3) 18(24.0)        
Nurse 59(78.7) 57(76.0) 0.85(0.39-1.84) 0.697 0.67(0.28-1.61) 0.370
Nature of employment        
Permanent 58(56.3) 48(57.8)        
Temporary 45(43.7) 35(42.2) 0.94(0.52-1.86) 0.835 0.60(0.28-1.28) 0.187
Religion        
Christian 102(99.0) 77(92.8)        
Muslim 1(1.0) 6(7.2) 7.94(0.94-67.39) 0.057 4.23(0.44-41.00) 0.21217
Significant at <0.05
Overall districts preparedness for 3 domainsOverall districts preparedness for 3 domains
18
DiscussionDiscussion
Infrastructure Preparedness
Majority of HFs were not prepared infrastructure
Infrastructure assessment for PHC concluded that there were
deficiencies in infrastructure of decentralized health systems (Scholz,
et al., 2015)
Lower health facilities such as H/C IVs, IIIs missed a robust
infrastructure system
 Polgreen, et al.,Concluded that small health facilities especially
those with less than 200 beds are always less prepared compared to
the bigger facilities
19
Discussion Cont’Discussion Cont’
Logistics preparedness cont’
PPEs weren’t observed at Health facilities implying that in case of suspected
index EVD case
Even taking highly pathogenic specimen from suspect will either take long to
be done, or person taking it will have to remove specimen without PPEs hence
making him/her ransom for a failed system
Health care workers’ knowledge level on EVD
There is low knowledge level about EVD among Health workers
In a related KAP in Nigeria, found that most health care workers had
inappropriate knowledge about EVD (Oluwookere, et al., 2015)
Very few health care workers knew that contact with clothes and beddings of
symptomatic EVD patients would be a direct mode of EVD transmission
 Precautionary measures are suboptimal
22
ConclusionConclusion
Infrastructural preparedness
The infrastructure is system is not prepared for any Ebola outbreak
response
Logistical capacity
Health care system is not logistically prepared for outbreak
response
Level of knowledge on Ebola etiology, control and prevention
Health care workers are not prepared in terms of knowledge for
Ebola identification, detection and thence outbreak response
Overall preparedness
Overall health care system of both districts is not prepared given
that all dimensions assessed were below cut offs.
23
RecommandationsRecommandations
Infrastructure
MoH should solicit resources and print and disseminate case definition
books, SOPs, and IEC materials and fact sheets about EVD disease to
health care workers
National stakeholders and District level should organize a multi-sectoral
approach simulation training exercise to appreciate need to be on alert at
all-times
Logistics and supply chain management
Critical logistics like; PPEs, triple package carriers for highly
pathogenic specimens and clear transportation mechanism should be
availed at all times
Knowledge on EVD etiology, prevention and control
Training should be tailored to address concerns of infection prevention
and control
Ebola biology, etiology, epidemiology and pathogenesis should be
designed for both in-service health workers and those in schools 24
AcknowledgementAcknowledgement
My lecturers at MUSPH
Supervisors; Mr. Abdullah Ali Halage
Dr. Sekimpi Deogratious, Dr. Innocent
Rwego
International Development Research
Centre(IDRC)-through One Health for East
and Central Africa(OHCEA)
OHCEA team
Health Care Workers in Kasese and Rubirizi25

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Preparedness of healthcare systems for Ebola outbreak response in Kaseses and Rubirizi districs, Western Uganda.

  • 1. Preparedness of Health Care Systems forPreparedness of Health Care Systems for Ebola Outbreak in Kasese and RubiriziEbola Outbreak in Kasese and Rubirizi Districts, Western UgandaDistricts, Western Uganda Kibuule Michael Makerere University College of Health Sciences- school of Public Health
  • 2. Background and IntroductionBackground and Introduction  Ebola virus disease constitutes the biggest public health problem worldwide and has occurred with increased frequency in the last five years  First insolated 1976 in Sub Saharan Africa. (W H O, 2014)  First incidence of EVD in Uganda happened in Gulu district Aug/2000- to- 01/2001, CFR of 80% (Lamunu, et al., 2004)  Preparedness is Knowledge and other capacities developed by individuals, communities, governments, professional response and recovery organizations (UNISDR, 2009)  Preparedness level of health care systems determine magnitude and impact of EVD outbreak (WHO, 2014) 2
  • 3. Literature ReviewLiterature Review  Health care system preparedness is optimal when it meets;  Infrastructural-triage space,  Rapid response teams,  EVD committees,  Isolation units,  Surveillance systems,  Case definition,  Knowledgeable of health workers,  Plus logistics  Ebola virus belongs to the Filoviridae family, Species are; Bundibugyo, Côte d’Ivoire, Reston, Sudan, and Zaire (WHO, 2014  Incubation period of EVD is 2–21 days, and it presents with early and late stages  Known risk factors for EVD outbreak- Behavioral, Cultural, and institutional, Physical contact and Poor Hand Hygiene 3
  • 5. ObjectivesObjectives General Objective To assess preparedness of health care system for Ebola outbreak response in Kasese and Rubirizi districts Specific Objectives To establish preparedness level of District Health Infrastructure to respond to EVD outbreak To determine logistical preparedness of health facilities to manage a suspected incident of Ebola disease case in Kasese and Rubirizi districts To establish health care workers’ level of knowledge on preparedness for containment of Ebola disease outbreak in Kasese and Rubirizi districts To determine overall level of preparedness for EVD outbreak and response in Kasese and Rubirizi districts 6
  • 6. MethodologyMethodology Study Site and PopulationStudy Site and Population Study population/Units All Hospital level facilities, all H/CIV level facilities, selected H/CIII facilities in Kasese district. Doctors, Medical Clinical Officers, Nurses, laboratory technicians, midwives and Nursing assistants 7
  • 7. MethodologyMethodology Study Design and Sampling ProceduresStudy Design and Sampling Procedures  Cross-sectional study with mixed methods  All hospitals and H/CIVs in both districts were purposively selected  Fifty percent H/CIIIs in each district were randomly selected using a ballot papers  List of H/CIIIs was obtained, ballot papers with their names written, then randomly selected until desired number was obtained  Number of HCWs selected using simple random sampling 8
  • 8. Data collection toolsData collection tools Category of respondents Data collection instruments Tool DHTs, DDMCs Key informants KI guide Departmental heads/In- charges FGDs FGD guide Health care workers Structured questionnaires Questionnaire Facility In-charges, hospital Administrators Facility checklists Checklist 9
  • 9. Data Management & AnalysisData Management & Analysis  Data was cleaned and triangulated before entry  Data entry was done from structured questionnaire using Epi-data  Data was then analyzed with STATA (Version.14)  Level of infrastructure preparedness was measured on a 14-point scale  All “Yes” responses scored 1 and the “No” responses score 0 10
  • 10. Data Analysis cont’Data Analysis cont’ Knowledge, a bivariate analysis was carried out using 2x2 table analysis Social demographic characteristics as independent variable Independent covariates were regressed on level of knowledge using equation of a straight line in multivariate logistic regression Level of knowledge as a dependent variable Unadjusted and adjusted odds ratio was used to assess the level of association at 0.05 significance level 13
  • 11. Analysis cont’Analysis cont’ Qualitative analysis. Researcher read through transcripts several times Drew categories and clustered data among themes Themed the categories as;-“Knowledge”, “logistics”, “Capacity” Summarized and displayed quotes In-depth reading and creating meaning from data was done  Researcher then developed conclusions from data 14
  • 12. Factor Level Kasese (n=148) Rubirizi (n=39) p-value N   (% )148 (%)39   Gender Female 55.4%(82) 56.4%(22) 0.91   Male 44.6%(66) 43.6%(17)   Age 20-30 51.0%(75) 58.3%(21) 0.73   31-40 28.6%(42) 25.0%(9)     41 and above 20.4%(30) 16.7%(6)   Religion Catholic 29.3%(43) 51.3%(20) 0.011   Muslim 4.1%(6) 2.6%(1)     Pentecostal 0.0%(0) 2.6%(1)     Pentecostal Baptist 2.7%(4) 0.0%(0)     Protestant 54.4%(80) 28.2%(11)     Seventh day Adventist 9.5%(14) 15.4%(6)   Education level Primary level 1.4%(2) 2.6%(1) 0.72   Secondary level 6.1%(9) 2.6%(1)     Tertiary level 83.0%(122) 82.1%(32)     University 9.5%(14) 12.8%(5)   Job designation Senior Medical officer 0.0%(0) 3.2%(1) 0.097   Medical officer 4.2%(5) 0.0%(0)     Senior medical clinical officer 20.2%(24) 12.9%(4)     Senior nursing officer 3.4%(4) 3.2%(1)     Enrolled registered midwife 37.1%(56) 67.7%(21)     lab technologist 16.8%(20) 12.9%(4)     other 8.4%(10) 0.0%(0)   Nature of employment Permanent 50.3%(74) 82.1%(32) <0.001   Temporary 43.5%(64) 12.8%(5)     Volunteer 6.1%(9) 2.6%(1)     others 0.0%(0) 2.6%(1)   16 Demographic of Health Care Workers in Kasese and Rubirizi Districts
  • 13. BivarianteBivariante Independent variables Knowledge level   COR(95% CI) P- value AOR (95% CI) P-value Low(n=104) High (83)         Gender         Female 61(58.7) 43(51.8)         Male 43(41.3) 40(48.2) 1.31(0.74-2.36) 0.350 0.88(.043-1.83) 0.747 Age         20-30 48(48.0) 48(57.0)         31-40 30(30.0) 21(26.3) 0.7(0.35-1.39) 0.308 0.65(0.28-1.46) 0.295 41 and above 22(22.0) 14(16.9) 0.64(0.29-1.39) 0.256 0.33(0.11-0.91) 0.032* Education level         Secondary level 11(10.6) 2(2.4)         Tertiary level 93(89.4) 80(97.6) 4.73(1.01-21.9) 0.047* 1 - Job designation         Clinician 16(21.3) 18(24.0)         Nurse 59(78.7) 57(76.0) 0.85(0.39-1.84) 0.697 0.67(0.28-1.61) 0.370 Nature of employment         Permanent 58(56.3) 48(57.8)         Temporary 45(43.7) 35(42.2) 0.94(0.52-1.86) 0.835 0.60(0.28-1.28) 0.187 Religion         Christian 102(99.0) 77(92.8)         Muslim 1(1.0) 6(7.2) 7.94(0.94-67.39) 0.057 4.23(0.44-41.00) 0.21217 Significant at <0.05
  • 14. Overall districts preparedness for 3 domainsOverall districts preparedness for 3 domains 18
  • 15. DiscussionDiscussion Infrastructure Preparedness Majority of HFs were not prepared infrastructure Infrastructure assessment for PHC concluded that there were deficiencies in infrastructure of decentralized health systems (Scholz, et al., 2015) Lower health facilities such as H/C IVs, IIIs missed a robust infrastructure system  Polgreen, et al.,Concluded that small health facilities especially those with less than 200 beds are always less prepared compared to the bigger facilities 19
  • 16. Discussion Cont’Discussion Cont’ Logistics preparedness cont’ PPEs weren’t observed at Health facilities implying that in case of suspected index EVD case Even taking highly pathogenic specimen from suspect will either take long to be done, or person taking it will have to remove specimen without PPEs hence making him/her ransom for a failed system Health care workers’ knowledge level on EVD There is low knowledge level about EVD among Health workers In a related KAP in Nigeria, found that most health care workers had inappropriate knowledge about EVD (Oluwookere, et al., 2015) Very few health care workers knew that contact with clothes and beddings of symptomatic EVD patients would be a direct mode of EVD transmission  Precautionary measures are suboptimal 22
  • 17. ConclusionConclusion Infrastructural preparedness The infrastructure is system is not prepared for any Ebola outbreak response Logistical capacity Health care system is not logistically prepared for outbreak response Level of knowledge on Ebola etiology, control and prevention Health care workers are not prepared in terms of knowledge for Ebola identification, detection and thence outbreak response Overall preparedness Overall health care system of both districts is not prepared given that all dimensions assessed were below cut offs. 23
  • 18. RecommandationsRecommandations Infrastructure MoH should solicit resources and print and disseminate case definition books, SOPs, and IEC materials and fact sheets about EVD disease to health care workers National stakeholders and District level should organize a multi-sectoral approach simulation training exercise to appreciate need to be on alert at all-times Logistics and supply chain management Critical logistics like; PPEs, triple package carriers for highly pathogenic specimens and clear transportation mechanism should be availed at all times Knowledge on EVD etiology, prevention and control Training should be tailored to address concerns of infection prevention and control Ebola biology, etiology, epidemiology and pathogenesis should be designed for both in-service health workers and those in schools 24
  • 19. AcknowledgementAcknowledgement My lecturers at MUSPH Supervisors; Mr. Abdullah Ali Halage Dr. Sekimpi Deogratious, Dr. Innocent Rwego International Development Research Centre(IDRC)-through One Health for East and Central Africa(OHCEA) OHCEA team Health Care Workers in Kasese and Rubirizi25