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Impact of COVID-19 on routine malaria indicators in Uganda: An interrupted time series analysis

BACKGROUND: In March 2020, the government of Uganda implemented a strict lockdown policy in response to the COVID-19 pandemic. We performed an interrupted time series analysis (ITSA) to assess whether major changes in healthcare seeking behavior, malaria burden, and case management occurred after th...

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Autores principales: Namuganga, Jane Frances, Briggs, Jessica, Roh, Michelle E, Okiring, Jaffer, Kisambira, Yasin, Sserwanga, Asadu, Kapisi, James Apollo, Arinaitwe, Emmanuel, Ebong, Chris, Ssewanyana, Isaac, Greenhouse, Bryan, Maiteki-Ssebuguzi, Catherine, Kamya, Moses R, Staedke, Sarah G, Dorsey, Grant, Nankabirwa, Joaniter I
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Journal Experts 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8382131/
https://www.ncbi.nlm.nih.gov/pubmed/34426808
http://dx.doi.org/10.21203/rs.3.rs-819495/v1
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author Namuganga, Jane Frances
Briggs, Jessica
Roh, Michelle E
Okiring, Jaffer
Kisambira, Yasin
Sserwanga, Asadu
Kapisi, James Apollo
Arinaitwe, Emmanuel
Ebong, Chris
Ssewanyana, Isaac
Greenhouse, Bryan
Maiteki-Ssebuguzi, Catherine
Kamya, Moses R
Staedke, Sarah G
Dorsey, Grant
Nankabirwa, Joaniter I
author_facet Namuganga, Jane Frances
Briggs, Jessica
Roh, Michelle E
Okiring, Jaffer
Kisambira, Yasin
Sserwanga, Asadu
Kapisi, James Apollo
Arinaitwe, Emmanuel
Ebong, Chris
Ssewanyana, Isaac
Greenhouse, Bryan
Maiteki-Ssebuguzi, Catherine
Kamya, Moses R
Staedke, Sarah G
Dorsey, Grant
Nankabirwa, Joaniter I
author_sort Namuganga, Jane Frances
collection PubMed
description BACKGROUND: In March 2020, the government of Uganda implemented a strict lockdown policy in response to the COVID-19 pandemic. We performed an interrupted time series analysis (ITSA) to assess whether major changes in healthcare seeking behavior, malaria burden, and case management occurred after the onset of the COVID-19 epidemic. METHODS: Individual level data from all outpatient visits occurring from April 2017 through March 2021 at 17 facilities were analyzed. Outcomes included total outpatient visits, malaria cases, non-malarial visits, proportion of visits with suspected malaria, proportion of patients tested using rapid diagnostic tests (RDTs), and proportion of malaria cases prescribed artemether-lumefantrine (AL). Pre-COVID trends measured over a three-year period were extrapolated into the post-COVID period (April 2020- March 2021) using Poisson regression with generalized estimating equations or fractional regression. Effects of COVID-19 were estimated over the 12-month post-COVID period by dividing observed values by the predicted values and expressed as ratios. RESULTS: A total of 1,442,737 outpatient visits were recorded. Malaria was suspected in 55.3% of visits and 98.8% of these had a malaria diagnostic test performed. ITSA showed no differences in the observed versus predicted total outpatient visits, malaria cases, non-malarial visits, or proportion of visits with suspected malaria. However, in the second six months of the post-COVID period, there was a smaller mean proportion of patients tested with RDTs compared to predicted (Relative Prevalence Ratio (RPR) = 0.87, CI [0.78, 0.97]) and a smaller mean proportion of malaria cases prescribed AL (RPR = 0.94, CI [0.90, 0.99]. CONCLUSIONS: There was evidence for a modest decrease in the proportion of RDTs used for malaria diagnosis and the proportion of patients prescribed AL in the second half of the post-COVID year, while other malaria indicators remained stable. Continued surveillance will be essential to monitor for changes in trends in malaria indicators so that Uganda can quickly and flexibly respond to challenges imposed by COVID-19.
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spelling pubmed-83821312021-08-24 Impact of COVID-19 on routine malaria indicators in Uganda: An interrupted time series analysis Namuganga, Jane Frances Briggs, Jessica Roh, Michelle E Okiring, Jaffer Kisambira, Yasin Sserwanga, Asadu Kapisi, James Apollo Arinaitwe, Emmanuel Ebong, Chris Ssewanyana, Isaac Greenhouse, Bryan Maiteki-Ssebuguzi, Catherine Kamya, Moses R Staedke, Sarah G Dorsey, Grant Nankabirwa, Joaniter I Res Sq Article BACKGROUND: In March 2020, the government of Uganda implemented a strict lockdown policy in response to the COVID-19 pandemic. We performed an interrupted time series analysis (ITSA) to assess whether major changes in healthcare seeking behavior, malaria burden, and case management occurred after the onset of the COVID-19 epidemic. METHODS: Individual level data from all outpatient visits occurring from April 2017 through March 2021 at 17 facilities were analyzed. Outcomes included total outpatient visits, malaria cases, non-malarial visits, proportion of visits with suspected malaria, proportion of patients tested using rapid diagnostic tests (RDTs), and proportion of malaria cases prescribed artemether-lumefantrine (AL). Pre-COVID trends measured over a three-year period were extrapolated into the post-COVID period (April 2020- March 2021) using Poisson regression with generalized estimating equations or fractional regression. Effects of COVID-19 were estimated over the 12-month post-COVID period by dividing observed values by the predicted values and expressed as ratios. RESULTS: A total of 1,442,737 outpatient visits were recorded. Malaria was suspected in 55.3% of visits and 98.8% of these had a malaria diagnostic test performed. ITSA showed no differences in the observed versus predicted total outpatient visits, malaria cases, non-malarial visits, or proportion of visits with suspected malaria. However, in the second six months of the post-COVID period, there was a smaller mean proportion of patients tested with RDTs compared to predicted (Relative Prevalence Ratio (RPR) = 0.87, CI [0.78, 0.97]) and a smaller mean proportion of malaria cases prescribed AL (RPR = 0.94, CI [0.90, 0.99]. CONCLUSIONS: There was evidence for a modest decrease in the proportion of RDTs used for malaria diagnosis and the proportion of patients prescribed AL in the second half of the post-COVID year, while other malaria indicators remained stable. Continued surveillance will be essential to monitor for changes in trends in malaria indicators so that Uganda can quickly and flexibly respond to challenges imposed by COVID-19. American Journal Experts 2021-08-18 /pmc/articles/PMC8382131/ /pubmed/34426808 http://dx.doi.org/10.21203/rs.3.rs-819495/v1 Text en https://creativecommons.org/licenses/by/4.0/License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License (https://creativecommons.org/licenses/by/4.0/) https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
spellingShingle Article
Namuganga, Jane Frances
Briggs, Jessica
Roh, Michelle E
Okiring, Jaffer
Kisambira, Yasin
Sserwanga, Asadu
Kapisi, James Apollo
Arinaitwe, Emmanuel
Ebong, Chris
Ssewanyana, Isaac
Greenhouse, Bryan
Maiteki-Ssebuguzi, Catherine
Kamya, Moses R
Staedke, Sarah G
Dorsey, Grant
Nankabirwa, Joaniter I
Impact of COVID-19 on routine malaria indicators in Uganda: An interrupted time series analysis
title Impact of COVID-19 on routine malaria indicators in Uganda: An interrupted time series analysis
title_full Impact of COVID-19 on routine malaria indicators in Uganda: An interrupted time series analysis
title_fullStr Impact of COVID-19 on routine malaria indicators in Uganda: An interrupted time series analysis
title_full_unstemmed Impact of COVID-19 on routine malaria indicators in Uganda: An interrupted time series analysis
title_short Impact of COVID-19 on routine malaria indicators in Uganda: An interrupted time series analysis
title_sort impact of covid-19 on routine malaria indicators in uganda: an interrupted time series analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8382131/
https://www.ncbi.nlm.nih.gov/pubmed/34426808
http://dx.doi.org/10.21203/rs.3.rs-819495/v1
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