| Title:
|
How to improve outbreak response: a case study of integrated outbreak analytics from Ebola in Eastern Democratic Republic of the Congo |
| Abstract:
|
The emerging field of outbreak analytics calls attention to the need for data from multiple sources to inform evidence-based decision making in managing infectious diseases outbreaks. To date these approaches have not systematically integrated evidence from social and behavioural sciences. During the 20182020 Ebola outbreak in Eastern Democratic Republic of the Congo an innovative solution to systematic and timely generation of integrated and actionable social science evidence emerged in the form of the Cellulle dAnalyse en Sciences Sociales (Social Sciences Analytics Cell) (CASS) a social science analytical cell. CASS worked closely with data scientists and epidemiologists operating under the Epidemiological Cell to produce integrated outbreak analytics (IOA) where quantitative epidemiological analyses were complemented by behavioural field studies and social science analyses to help better explain and understand drivers and barriers to outbreak dynamics. The primary activity of the CASS was to conduct operational social science analyses that were useful to decision makers. This included ensuring that research questions were relevant driven by epidemiological data from the field that research could be conducted rapidly (ie often within days) that findings were regularly and systematically presented to partners and that recommendations were co-developed with response actors. The implementation of the recommendations based on CASS analytics was also monitored over time to measure their impact on response operations. This practice paper presents the CASS logic model developed through a field-based externally led consultation and documents key factors contributing to the usefulness and adaption of CASS and IOA to guide replication for future outbreaks. |
| Published:
|
2021-08-19 |
| Journal:
|
BMJ Glob Health |
| DOI:
|
10.1136/bmjgh-2021-006736 |
| DOI_URL:
|
http://doi.org/10.1136/bmjgh-2021-006736 |
| Author Name:
|
Carter Simone E |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/carter_simone_e |
| Author Name:
|
Ahuka Mundeke Steve |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/ahuka_mundeke_steve |
| Author Name:
|
Pfaffmann Zambruni Jrme |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/pfaffmann_zambruni_jrme |
| Author Name:
|
Navarro Colorado Carlos |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/navarro_colorado_carlos |
| Author Name:
|
van Kleef Esther |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/van_kleef_esther |
| Author Name:
|
Lissouba Pascale |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/lissouba_pascale |
| Author Name:
|
Meakin Sophie |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/meakin_sophie |
| Author Name:
|
le Polain de Waroux Olivier |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/le_polain_de_waroux_olivier |
| Author Name:
|
Jombart Thibaut |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/jombart_thibaut |
| Author Name:
|
Mossoko Mathias |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/mossoko_mathias |
| Author Name:
|
Bulemfu Nkakirande Dorothe |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/bulemfu_nkakirande_dorothe |
| Author Name:
|
Esmail Marjam |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/esmail_marjam |
| Author Name:
|
Earle Richardson Giulia |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/earle_richardson_giulia |
| Author Name:
|
Degail Marie Amelie |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/degail_marie_amelie |
| Author Name:
|
Umutoni Chantal |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/umutoni_chantal |
| Author Name:
|
Anoko Julienne Ngoundoung |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/anoko_julienne_ngoundoung |
| Author Name:
|
Gobat Nina |
| Author link:
|
https://covid19-data.nist.gov/pid/rest/local/author/gobat_nina |
| sha:
|
e2f60213b2765198e9365fc6058ac7d0aff0e3a4 |
| license:
|
cc-by-nc |
| license_url:
|
https://creativecommons.org/licenses/by-nc/4.0/ |
| source_x:
|
Medline; PMC |
| source_x_url:
|
https://www.medline.com/https://www.ncbi.nlm.nih.gov/pubmed/ |
| pubmed_id:
|
34413078 |
| pubmed_id_url:
|
https://www.ncbi.nlm.nih.gov/pubmed/34413078 |
| pmcid:
|
PMC8380808 |
| pmcid_url:
|
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8380808 |
| url:
|
https://www.ncbi.nlm.nih.gov/pubmed/34413078/
https://doi.org/10.1136/bmjgh-2021-006736 |
| has_full_text:
|
TRUE |
| Keywords Extracted from Text Content:
|
Foreign
IPC
COVID-19
donors
non-government organisations
In-country
SM, PL
Equateur
recipients
IOA
cells
women
Cell
Epi Info
IOA cell
UNICEFdeployed
human
pillar
TJ
BZR02530
measles
Control-Water Sanitation Hygiene (IPC-WASH
IPC-WASH
ToRs
CNC
MONITO
SA-M
DBN
Bunia
IRC
polio
Congo
EVK
language
Goma
hostpots
cell
5-7
DRC
Patient
UK Foreign
MSF-Epicentre
cholera
OlPdW
NGOs
JNA
CDC-Atlanta
UNICEF
funds
CU
GE-R
participants
COVID-19 Public Health |
| Extracted Text Content in Record:
|
First 5000 Characters:The 2018-2020 Ebola outbreak in Eastern Democratic Republic of the Congo (DRC) was the second largest in recorded history. 1 By the time the outbreak was declared over on 25 June 2020, there had been 3481 confirmed cases, including 2299 fatalities, in an area affected by a protracted crisis due to long standing political tensions and conflicts, and widespread historic mistrust in government and public authority. 2 The DRC is a country at high risk of epidemics; at the time of the Summary box ► During the 2018-2020 Ebola outbreak in Eastern Democratic Republic of the Congo, an innovative solution to systematic and timely generation of integrated and actionable social science evidence emerged in the form of the Cellulle d'Analyse en Sciences Sociales (CASS). ► The CASS worked closely with data scientists and epidemiologists operating under the Epidemiological Cell to produce integrated outbreak analytics (IOA). ► IOA is a transdisciplinary approach where quantitative epidemiological analyses, health services and systems data, behavioural field studies, social science analyses, contextual data (eg, socioeconomic, population data) and operational programmes data are analysed holistically to help better explain and understand drivers and barriers to outbreak dynamics. ► The CASS conducted rapid, operational social science analyses to complement epidemiological, health services and programmes data which were analysed in an integrated manner and were systematically presented and used to inform response activities and strategies. ► The implementation of the recommendations based on CASS analytics was monitored over time, to measure the use of evidence and its impact on response operations.
10th Ebola outbreak, the Eastern region experienced concurrent epidemics of polio, cholera, measles and plague. 3 4 Coordinating an Ebola response in this challenging context required decision makers to have situational awareness of multiple aspects of a dynamic and fast-paced public health crisis from which to make timely strategic and operational decisions. 5 6 The emerging field of outbreak analytics calls attention to the need for data from multiple sources to inform evidence-informed decision making in managing infectious diseases outbreaks. 7 8 To date, these approaches have not systematically integrated evidence from social and behavioural sciences as a core part of integrated outbreak analytics (IOA). 9 During the 2018-2020 Ebola outbreak, an innovative solution to systematic and timely generation of integrated and actionable social science evidence emerged in the form of the Cellulle d'Analyse en Sciences Sociales (CASS), a social science analytics cell. CASS was embedded within the national response structure and worked closely with data scientists and epidemiologists operating under the Epidemiological Cell to produce IOA, where quantitative epidemiological analyses were complemented by behavioural field studies and social science analyses to help better explain and understand drivers and barriers to outbreak dynamics. CASS delivered 58 integrated studies, which led to 112 evidence-informed recommendations co-developed with response pillars to improve and adapt response interventions and strategies.
This paper details the operational processes of the CASS based on an extensive review of CASS documents and tools, strategies and reports and a 2-week externally led consultation (NG University of Oxford), funded by the Wellcome Trust and UK Foreign, Commonwealth and Development Office. This consultation included interviews with 79 stakeholders from different levels of the Ebola outbreak response in the DRC to understand their views on key characteristics of the CASS model, usefulness and challenges as well as aspects that could be improved and what would be needed to replicate the model for future outbreaks. The outcome of this consultation led to refinements in how CASS achieved its outcomes and impact, and informed subsequent CASS support in the DRC to COVID-19, cholera, the 11th and 12th Ebola outbreaks as well as to the Ebola outbreak in Guinea (April 2021). [10] [11] [12] THE ORIGINS OF CASS The CASS developed organically and in response to needs expressed by response actors to better understand the determinants of epidemiological trends, transmission dynamics and differences across affected communities, from a holistic epidemiological, social and behavioural perspective. The studies which led to a more formal set up of CASS started in October 2018, with a UNICEFdeployed social epidemiologist (SEC). In October 2018, SEC conducted a qualitative study to better understand the situation for pregnant and lactating women who were not eligible for the vaccine and not reported by vaccination or surveillance teams. This first study directly supported response pillars including psychosocial, surveillance, vaccination and epidemiological teams to better integrate those non-eligible for the vaccine. In November 2018, Medair, an |
| Keywords Extracted from PMC Text:
|
recommendations3
DRC
studies2
Cell
history.1
measles
human
IRC
Control-Water Sanitation Hygiene (IPC-WASH
's
1).14
ToRs
IPC
recipients
MONITO
participants
COVID-19 Public Health
NGOs
included1
women's
Epi Info
Congo
UK Foreign
plague.3 4
women
(IOA).9
UNICEF-deployed
IOA
funds
pillar
donors
MSF-Epicentre
Equateur
conflict).16 A
cell
UNICEF
IOA cell
results.14
language
polio
and4
5–7
non-government organisations
cholera
In-country
COVID-19
CDC-Atlanta |
| Extracted PMC Text Content in Record:
|
First 5000 Characters:The 2018–2020 Ebola outbreak in Eastern Democratic Republic of the Congo (DRC) was the second largest in recorded history.1 By the time the outbreak was declared over on 25 June 2020, there had been 3481 confirmed cases, including 2299 fatalities, in an area affected by a protracted crisis due to long standing political tensions and conflicts, and widespread historic mistrust in government and public authority.2 The DRC is a country at high risk of epidemics; at the time of the 10th Ebola outbreak, the Eastern region experienced concurrent epidemics of polio, cholera, measles and plague.3 4 Coordinating an Ebola response in this challenging context required decision makers to have situational awareness of multiple aspects of a dynamic and fast-paced public health crisis from which to make timely strategic and operational decisions.5 6
The emerging field of outbreak analytics calls attention to the need for data from multiple sources to inform evidence-informed decision making in managing infectious diseases outbreaks.7 8 To date, these approaches have not systematically integrated evidence from social and behavioural sciences as a core part of integrated outbreak analytics (IOA).9 During the 2018–2020 Ebola outbreak, an innovative solution to systematic and timely generation of integrated and actionable social science evidence emerged in the form of the Cellulle d'Analyse en Sciences Sociales (CASS), a social science analytics cell. CASS was embedded within the national response structure and worked closely with data scientists and epidemiologists operating under the Epidemiological Cell to produce IOA, where quantitative epidemiological analyses were complemented by behavioural field studies and social science analyses to help better explain and understand drivers and barriers to outbreak dynamics. CASS delivered 58 integrated studies, which led to 112 evidence-informed recommendations co-developed with response pillars to improve and adapt response interventions and strategies.
This paper details the operational processes of the CASS based on an extensive review of CASS documents and tools, strategies and reports and a 2-week externally led consultation (NG University of Oxford), funded by the Wellcome Trust and UK Foreign, Commonwealth and Development Office. This consultation included interviews with 79 stakeholders from different levels of the Ebola outbreak response in the DRC to understand their views on key characteristics of the CASS model, usefulness and challenges as well as aspects that could be improved and what would be needed to replicate the model for future outbreaks. The outcome of this consultation led to refinements in how CASS achieved its outcomes and impact, and informed subsequent CASS support in the DRC to COVID-19, cholera, the 11th and 12th Ebola outbreaks as well as to the Ebola outbreak in Guinea (April 2021).10–12
The CASS developed organically and in response to needs expressed by response actors to better understand the determinants of epidemiological trends, transmission dynamics and differences across affected communities, from a holistic epidemiological, social and behavioural perspective. The studies which led to a more formal set up of CASS started in October 2018, with a UNICEF-deployed social epidemiologist (SEC). In October 2018, SEC conducted a qualitative study to better understand the situation for pregnant and lactating women who were not eligible for the vaccine and not reported by vaccination or surveillance teams. This first study directly supported response pillars including psychosocial, surveillance, vaccination and epidemiological teams to better integrate those non-eligible for the vaccine. In November 2018, Medair, an Ebola healthcare provider, requested support to better understand reasons for non-reporting or referral of suspected Ebola cases in one of their supported healthcare facilities.13 This request led to the first CASS partnership study, a qualitative study with healthcare workers and community members to better understand barriers to healthcare access. SEC led this study and provided training for Medair staff to lead future groups. In January 2019, partnerships continued to expand and included working with the Infection Prevention and Control-Water Sanitation Hygiene (IPC-WASH) pillar and WHO IPC teams to conduct studies to better understand perceptions and use of healthcare facilities and IPC measures and again, this reinforced a multiactor approach to the collection and use of data. The CASS was able to rapidly provide evidence and understanding that was relevant and adapted, responding to critical questions. The inclusion of a broad range of response actors, including government and non-government organisations within the CASS studies, reinforced relationships with the end line data users, contributing to CASS credibility and trust.
A retrospective review of the CASS allowed for identifying the resources necessary to replicate the experience |
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