Preparedness of Health Care Systems for Ebola Outbreak Response in Kasese and Rubirizi districts, Western Uganda Article Swipe
YOU?
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· 2020
· Open Access
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· DOI: https://doi.org/10.21203/rs.3.rs-30845/v2
Background: The level of preparedness of the health care workers, the health facility and the entire health system determines the magnitude of the impact of an Ebola Virus Disease (EVD) outbreak as demonstrated by the West African Ebola outbreak. The objective of the study was to assess preparedness of the health care facilities and identify appropriate preparedness measures for Ebola outbreak response in Kasese and Rubirizi districts in western Uganda. Methods: A cross sectional descriptive study was conducted by interviewing 189 health care workers using a structured questionnaire and visits to 22 health facilities to determine the level of health care system preparedness to EVD outbreak. District level infrastructure capabilities, existence of health facility logistics and supplies, and health care workers’ knowledge of EVD was assessed. EVD Preparedness was assessed on infrastructure and logistical capabilities and the level of knowledge of an individual health work about the etiology, control and prevention of EVD. Results: Twelve out of the 22 of the health facilities, especially health center III’s and IV’s, did not have a line budget to respond to EVD when there was a threat of EVD in nearby country. The majority (n = 13) of the facilities did not have the following: case definition books, rapid response teams and/or committees, burial teams, simulation drills. There were no personal protective equipment that could be used within 8 hours in case of an EVD outbreak fourteen of the health facilities. All facilities did not have Viral Hemorrhagic Fever (VHF) incident management centers, isolation units, guidelines for burial, and one-meter distance between health care worker and patient during triage. Overall, 54% (n = 102) of health care workers (HCWs) did not know the incubation period of EVD. Health Care workers who had tertiary education (aOR = 5.79; CI = 1.79 – 18.70; p = 0.003) were more likely to know about the biology incubation period, causes and prevention of EVD. Conclusions : Feedback on the level of preparedness for the rural districts helps inform strategies for building capacity of these health centers in terms of infrastructure, logistics and improving knowledge of health care workers.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-30845/v2
- https://www.researchsquare.com/article/rs-30845/v2.pdf?c=1605558046000
- OA Status
- green
- References
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- Related Works
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- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4214676619Canonical identifier for this work in OpenAlex
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https://doi.org/10.21203/rs.3.rs-30845/v2Digital Object Identifier
- Title
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Preparedness of Health Care Systems for Ebola Outbreak Response in Kasese and Rubirizi districts, Western Uganda Work title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-11-16Full publication date if available
- Authors
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Michael Kibuule, Deogratias Sekimpi, Aggrey Agaba, Abdullah Ali Halage, Michael Jonga, Leonard Manirakiza, Catherine Kansiime, Dominic A. Travis, Katharine M. Pelican, Innocent B. RwegoList of authors in order
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https://doi.org/10.21203/rs.3.rs-30845/v2Publisher landing page
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https://www.researchsquare.com/article/rs-30845/v2.pdf?c=1605558046000Direct link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://www.researchsquare.com/article/rs-30845/v2.pdf?c=1605558046000Direct OA link when available
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Preparedness, Medicine, Political science, LawTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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37Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.during | 265 |
| abstract_inverted_index.entire | 16 |
| abstract_inverted_index.health | 8, 12, 17, 51, 82, 93, 100, 113, 119, 144, 162, 165, 237, 260, 273, 338, 349 |
| abstract_inverted_index.impact | 24 |
| abstract_inverted_index.inform | 331 |
| abstract_inverted_index.likely | 305 |
| abstract_inverted_index.nearby | 188 |
| abstract_inverted_index.period | 282 |
| abstract_inverted_index.system | 18, 102 |
| abstract_inverted_index.teams, | 212 |
| abstract_inverted_index.threat | 184 |
| abstract_inverted_index.units, | 252 |
| abstract_inverted_index.visits | 90 |
| abstract_inverted_index.within | 225 |
| abstract_inverted_index.worker | 262 |
| abstract_inverted_index.African | 37 |
| abstract_inverted_index.Disease | 29 |
| abstract_inverted_index.III’s | 167 |
| abstract_inverted_index.IV’s, | 169 |
| abstract_inverted_index.Uganda. | 70 |
| abstract_inverted_index.between | 259 |
| abstract_inverted_index.biology | 310 |
| abstract_inverted_index.burial, | 255 |
| abstract_inverted_index.centers | 339 |
| abstract_inverted_index.control | 149 |
| abstract_inverted_index.drills. | 214 |
| abstract_inverted_index.patient | 264 |
| abstract_inverted_index.period, | 312 |
| abstract_inverted_index.respond | 177 |
| abstract_inverted_index.triage. | 266 |
| abstract_inverted_index.western | 69 |
| abstract_inverted_index.workers | 84, 275, 287 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.District | 107 |
| abstract_inverted_index.Feedback | 320 |
| abstract_inverted_index.Methods: | 71 |
| abstract_inverted_index.Overall, | 267 |
| abstract_inverted_index.Results: | 154 |
| abstract_inverted_index.Rubirizi | 66 |
| abstract_inverted_index.assessed | 130 |
| abstract_inverted_index.building | 334 |
| abstract_inverted_index.capacity | 335 |
| abstract_inverted_index.centers, | 250 |
| abstract_inverted_index.country. | 189 |
| abstract_inverted_index.distance | 258 |
| abstract_inverted_index.facility | 13, 114 |
| abstract_inverted_index.fourteen | 234 |
| abstract_inverted_index.identify | 55 |
| abstract_inverted_index.incident | 248 |
| abstract_inverted_index.majority | 191 |
| abstract_inverted_index.measures | 58 |
| abstract_inverted_index.outbreak | 31, 61, 233 |
| abstract_inverted_index.personal | 218 |
| abstract_inverted_index.response | 62, 207 |
| abstract_inverted_index.tertiary | 290 |
| abstract_inverted_index.workers, | 10 |
| abstract_inverted_index.workers. | 351 |
| abstract_inverted_index.assessed. | 126 |
| abstract_inverted_index.conducted | 78 |
| abstract_inverted_index.determine | 96 |
| abstract_inverted_index.districts | 67, 329 |
| abstract_inverted_index.education | 291 |
| abstract_inverted_index.equipment | 220 |
| abstract_inverted_index.etiology, | 148 |
| abstract_inverted_index.existence | 111 |
| abstract_inverted_index.improving | 346 |
| abstract_inverted_index.isolation | 251 |
| abstract_inverted_index.knowledge | 122, 140, 347 |
| abstract_inverted_index.logistics | 115, 344 |
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| abstract_inverted_index.objective | 41 |
| abstract_inverted_index.one-meter | 257 |
| abstract_inverted_index.outbreak. | 39, 106 |
| abstract_inverted_index.sectional | 74 |
| abstract_inverted_index.supplies, | 117 |
| abstract_inverted_index.definition | 204 |
| abstract_inverted_index.determines | 19 |
| abstract_inverted_index.especially | 164 |
| abstract_inverted_index.facilities | 53, 94, 197, 240 |
| abstract_inverted_index.following: | 202 |
| abstract_inverted_index.guidelines | 253 |
| abstract_inverted_index.incubation | 281, 311 |
| abstract_inverted_index.individual | 143 |
| abstract_inverted_index.logistical | 134 |
| abstract_inverted_index.management | 249 |
| abstract_inverted_index.prevention | 151, 315 |
| abstract_inverted_index.protective | 219 |
| abstract_inverted_index.simulation | 213 |
| abstract_inverted_index.strategies | 332 |
| abstract_inverted_index.structured | 87 |
| abstract_inverted_index.workers’ | 121 |
| abstract_inverted_index.Background: | 1 |
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| abstract_inverted_index.Hemorrhagic | 245 |
| abstract_inverted_index.appropriate | 56 |
| abstract_inverted_index.committees, | 210 |
| abstract_inverted_index.descriptive | 75 |
| abstract_inverted_index.facilities, | 163 |
| abstract_inverted_index.facilities. | 238 |
| abstract_inverted_index.Preparedness | 128 |
| abstract_inverted_index.capabilities | 135 |
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| abstract_inverted_index.interviewing | 80 |
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| abstract_inverted_index.capabilities, | 110 |
| abstract_inverted_index.questionnaire | 88 |
| abstract_inverted_index.infrastructure | 109, 132 |
| abstract_inverted_index.infrastructure, | 343 |
| cited_by_percentile_year | |
| countries_distinct_count | 2 |
| institutions_distinct_count | 10 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.4300000071525574 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.19482625 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |