Data innovation in response to COVID-19 in Somalia: application of a syndromic case definition and rapid mortality assessment method

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ABSTRACT

Background

During the COVID-19 pandemic, the importance of reliable public health data has been highlighted, as well as the multiple challenges in collecting it, especially in low income and conflict-affected countries. Somalia reported its first confirmed case of COVID-19 on 16 March 2020 and has experienced fluctuating infection levels since then.

Objectives

To monitor the impact of COVID-19 on beneficiaries of a long-term cash transfer programme in Somalia and assess the utility of a syndromic score case definition and rapid mortality surveillance tool.

Methods

Five rounds of telephone interviews were conducted from June 2020 – April 2021 with 1,046–1,565 households participating in a cash transfer programme. The incidence of COVID-19 symptoms and all-cause mortality were recorded. Carers of the deceased were interviewed a second time using a rapid verbal autopsy questionnaire to determine symptoms preceding death. Data were recorded on mobile devices and analysed using COVID Rapid Mortality Surveillance (CRMS) software and R.

Results

The syndromic score case definition identified suspected symptomatic cases that were initially confined to urban areas but then spread widely throughout Somalia. During the first wave, the peak syndromic case rate (311 cases/million people/day) was 159 times higher than the average laboratory confirmed case rate reported by WHO for the same period. Suspected COVID-19 deaths peaked at 14.3 deaths/million people/day, several weeks after the syndromic case rate. Crude and under-five death rates did not cross the respective emergency humanitarian thresholds (1 and 2 deaths/10,000 people/day).

Conclusion

Use of telephone interviews to collect data on the evolution of COVID-19 outbreaks is a useful additional approach that can complement laboratory testing and mortality data from the health system. Further work to validate the syndromic score case definition and CRMS is justified.

KEYWORDS:

• Somalia
• Covid-19
• surveillance system
• mortality
• syndromic case definition

Responsible Editor Stig Wall

Responsible Editor Stig Wall

Acknowledgments

The authors would like to acknowledge the participants of the Safety Net Pilot beneficiaries who contributed the data. Special thanks go to consortium members who reviewed the findings of the BRCiS monitoring system.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Capacity building & equity

Peter Byass often reflected on the very concept of ‘global health’ and strove to promote models of global health practice that addressed gaps in infrastructure, management, and human capital in LMICs. His well-used and much-stamped passports reflect his commitment to collaboration, partnerships and the importance of in-person relationships to build capacity. He was very conscious of and perhaps somewhat bewildered by academics from high-income countries ‘parachuting’ into low-income countries to set up systems or extract data with little or no effort to improve research capacity or to meaningfully engage with the people working and living there, who are undoubtedly better placed to define issues of importance and interpret data in relation to the on-the-ground context. Peter worked to amplify the local voice and build capacity for measurement and solutions to local problems. This recognised the fact that locally owned solutions are more likely to be sustainable, to have buy-in from critical stakeholders and, ultimately, to succeed in improving health.

The legacy of Peter’s ethos is apparent in our paper describing a pragmatic tool to understand the burden of COVID-19 in Somalia. The world’s ongoing failure to measure mortality, with the poorest populations remaining uncounted, is a matter of equity and basic human rights and it is of heightened importance during the current pandemic. We know poorer people are much less likely to have their deaths recorded, and this introduces a strong bias into health data. Our paper describes the rapid development and pragmatic adaptation of a locally run call-centre system of monitoring and evaluation built onto an existing social welfare scheme, which has allowed measurement among the poorest 10% of a community in a fragile country at the time of the COVID-19 pandemic. Our study population is likely to be under represented in hospital data or official COVID statistics and our innovative, equity-sensitive information systems – including the COVID-19 Rapid Mortality Surveillance tools on which Peter was working until his death – directly address such bias and inequity by giving this population a voice and ‘making them count’. Collaborative discussion and interpretation between academics, a non-governmental organisation, the Somali government and local communities have enabled meaningful use of these data and the initiative represents a commitment to local ownership and responsiveness to issues of global health importance.

Ethics and consent

This study was approved by the Mogadishu Ministry of Health and Human Services, reference number MOH&HS/DGO/0908/May/2021. All participants consented to take part in the data collection process.

Paper context

Somalia has been affected by three waves of COVID-19 infections, but the case rate and cause-specific deaths can only be approximated due to low levels of testing. We estimated the symptomatic case and death rates due to COVID-19 using a syndromic score case definition and rapid verbal autopsy interviews. The suspected symptomatic case rate was approximately 99 times higher than the laboratory confirmed rate reported by WHO. This approach shows promise for monitoring the COVID-19 pandemic in low resource settings.

Supplementary material

Supplemental data for this article can be accessed here

Additional information

Funding

The implementation of the Building Resilient Communities in Somalia (BRCiS) monitoring system was funded by the UK FCDO. No specific funding was made available for the writing of this paper.

Notes on contributors

Mohamed Jelle

AS, MJ, BN, CGE, and EF contributed to the design of the study. MJ, MH, and DF managed and supervised the data collection. AS, FM, and GA conducted data management and analysis. AS and EF wrote the manuscript with support from all other authors. All authors contributed to interpretation of the results, reviewed and edited the manuscript and approved the submission.