Turning mobile big data insights into public health responses in times of pandemics: Lessons learnt from the Democratic Republic of the Congo
In low-income countries like the Democratic Republic of the Congo (DRC)—where data is scarce and national statistics offices often under-resourced—aggregated and anonymised mobile operators’ data can provide vital insights for decision-makers to promptly respond to both prevailing and new pandemics,...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
2022-01-01
|
| Series: | Data & Policy |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S2632324921000304/type/journal_article |
| _version_ | 1811156509444276224 |
|---|---|
| author | Chloe Gueguen Nicolas Snel Eric Mutonji |
| author_facet | Chloe Gueguen Nicolas Snel Eric Mutonji |
| author_sort | Chloe Gueguen |
| collection | DOAJ |
| description | In low-income countries like the Democratic Republic of the Congo (DRC)—where data is scarce and national statistics offices often under-resourced—aggregated and anonymised mobile operators’ data can provide vital insights for decision-makers to promptly respond to both prevailing and new pandemics, such as COVID-19. Yet, while research on possible applications of mobile big data (MBD) analytics for COVID-19 is growing, there is still little evidence on how such use cases are actually being adopted by governmental authorities and how MBD insights can effectively be turned into informed public health actions in times of crises. This four-part commentary paper aims to bridge such literature gaps, by sharing lessons learnt from the DRC, whereby Congolese public health authorities, through a steep learning curve, have initiated a public–private sector dialogue with local mobile network operators (MNOs) and their ecosystem partners to leverage population mobility insights for COVID-19 policy-making. After having set the scene on the policy relevance of MBD analytics in the context of the DRC in the first section, the paper will then detail four key enablers that contributed, since March 2020, to accelerate Congolese authorities’ uptake of MBD, thus effectively increasing preparedness for future pandemics. Thirdly, we showcase concreate use-cases where “readiness-to-use” has actually translated into actual “usage” and “adoption” for decision-making, while introducing other use cases currently under development. Finally, we explore challenges when harnessing telco big data for decision-making with the ultimate aim to share lessons to replicate the successes and steer the development of MBD for social good in other low-income countries. |
| first_indexed | 2024-04-10T04:51:49Z |
| format | Article |
| id | doaj.art-ab2a11dd50ec486bafd4b77097d98bd7 |
| institution | Directory Open Access Journal |
| issn | 2632-3249 |
| language | English |
| last_indexed | 2024-04-10T04:51:49Z |
| publishDate | 2022-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Data & Policy |
| spelling | doaj.art-ab2a11dd50ec486bafd4b77097d98bd72023-03-09T12:31:38ZengCambridge University PressData & Policy2632-32492022-01-01410.1017/dap.2021.30Turning mobile big data insights into public health responses in times of pandemics: Lessons learnt from the Democratic Republic of the CongoChloe Gueguen0Nicolas Snel1https://orcid.org/0000-0001-5248-8114Eric Mutonji2The GSMA Foundation AI for Impact (AI4I) Team, Dakar, SenegalThe GSMA Foundation AI for Impact (AI4I) Team, London, United KingdomAgence Nationale d’Ingénierie Clinique, de l’Information et de l’Informatique de Santé (ANICiiS), Kinshasa, Democratic Republic of the CongoIn low-income countries like the Democratic Republic of the Congo (DRC)—where data is scarce and national statistics offices often under-resourced—aggregated and anonymised mobile operators’ data can provide vital insights for decision-makers to promptly respond to both prevailing and new pandemics, such as COVID-19. Yet, while research on possible applications of mobile big data (MBD) analytics for COVID-19 is growing, there is still little evidence on how such use cases are actually being adopted by governmental authorities and how MBD insights can effectively be turned into informed public health actions in times of crises. This four-part commentary paper aims to bridge such literature gaps, by sharing lessons learnt from the DRC, whereby Congolese public health authorities, through a steep learning curve, have initiated a public–private sector dialogue with local mobile network operators (MNOs) and their ecosystem partners to leverage population mobility insights for COVID-19 policy-making. After having set the scene on the policy relevance of MBD analytics in the context of the DRC in the first section, the paper will then detail four key enablers that contributed, since March 2020, to accelerate Congolese authorities’ uptake of MBD, thus effectively increasing preparedness for future pandemics. Thirdly, we showcase concreate use-cases where “readiness-to-use” has actually translated into actual “usage” and “adoption” for decision-making, while introducing other use cases currently under development. Finally, we explore challenges when harnessing telco big data for decision-making with the ultimate aim to share lessons to replicate the successes and steer the development of MBD for social good in other low-income countries.https://www.cambridge.org/core/product/identifier/S2632324921000304/type/journal_articleAfricabig dataCOVID-19Democratic Republic of the Congoe-health |
| spellingShingle | Chloe Gueguen Nicolas Snel Eric Mutonji Turning mobile big data insights into public health responses in times of pandemics: Lessons learnt from the Democratic Republic of the Congo Data & Policy Africa big data COVID-19 Democratic Republic of the Congo e-health |
| title | Turning mobile big data insights into public health responses in times of pandemics: Lessons learnt from the Democratic Republic of the Congo |
| title_full | Turning mobile big data insights into public health responses in times of pandemics: Lessons learnt from the Democratic Republic of the Congo |
| title_fullStr | Turning mobile big data insights into public health responses in times of pandemics: Lessons learnt from the Democratic Republic of the Congo |
| title_full_unstemmed | Turning mobile big data insights into public health responses in times of pandemics: Lessons learnt from the Democratic Republic of the Congo |
| title_short | Turning mobile big data insights into public health responses in times of pandemics: Lessons learnt from the Democratic Republic of the Congo |
| title_sort | turning mobile big data insights into public health responses in times of pandemics lessons learnt from the democratic republic of the congo |
| topic | Africa big data COVID-19 Democratic Republic of the Congo e-health |
| url | https://www.cambridge.org/core/product/identifier/S2632324921000304/type/journal_article |
| work_keys_str_mv | AT chloegueguen turningmobilebigdatainsightsintopublichealthresponsesintimesofpandemicslessonslearntfromthedemocraticrepublicofthecongo AT nicolassnel turningmobilebigdatainsightsintopublichealthresponsesintimesofpandemicslessonslearntfromthedemocraticrepublicofthecongo AT ericmutonji turningmobilebigdatainsightsintopublichealthresponsesintimesofpandemicslessonslearntfromthedemocraticrepublicofthecongo |