Background

The Massachusetts Institute of Technology Governance Lab (MIT GOV/LAB) and the Institute for Governance Reform (IGR), in partnership with Sierra Leone’s Directorate of Science, Technology and Innovation (DSTI) and Ministry of Finance’s Research and Delivery Division (MoF-RDD), conducted a nationally representative survey of 2,395 respondents 11-18 April 2020 to gather critical information on citizens’ Covid-19 awareness and preparedness across all 16 districts. Note: Below are preliminary results (pending verification and subject to change). Additional analyses forthcoming. Follow-up phone surveys are planned to inform a series of research briefs.

Suggested Citation

MIT GOV/LAB, IGR, DSTI, and MoF-RDD. 15 MAY 2020. “Preliminary Results from Rapid Survey to Inform Covid-19 Response in Sierra Leone.” Research Brief, Massachusetts Institute of Technology Governance Lab (United States), Institute for Governance Reform (Sierra Leone), and Sierra Leone’s Directorate of Science, Technology & Innovation and Ministry of Finance’s Research & Delivery Division.

Contributors

Lily L. Tsai, Professor, Massachusetts Institute of Technology, and Faculty Director, MIT Governance Lab (MIT GOV/LAB)
Leah Rosenzweig, Research Fellow, Institute for Advanced Study in Toulouse (IAST) and Research Affiliate, MIT GOV/LAB
Alisa Zomer, Assistant Director, MIT GOV/LAB
Andrew Lavali, Executive Director, Institute for Governance Reform [IGR]
Fredline M’Cormack-Hale, Associate Professor, Seton Hall University and Research and Policy Director, IGR
PJ Cole, Head of Project Design and Delivery at DSTI and Associate, Tony Blair Institute
Yakama Manty Jones, Director of Research & Delivery, Sierra Leone’s Ministry of Finance

Priority Policy Questions

The survey covers a wide range of topics related to Covid-19 and was developed to address priority policy questions to inform national and district-level actions. Relevant tables and maps notes.

1. What do citizens already know about Coronavirus?  (see Table 1)
2. What public health messages need to be communicated as a priority? (Table 1)
3. Which districts need targeted messaging for Coronavirus response? (Maps 1, 2, 3)
4. How long should the lockdown be? (Table 1)
5. Which districts are most at risk of going hungry during a lockdown? (Map 8)
6. Which districts are most vulnerable to the impacts of lockdown? (Maps 5, 6)
7. What is the capacity for community-led coronavirus response by district? (Map 5)

Findings at the National Level

Table 1: Findings at the National Level

Maps – Findings by District

Knowledge of Covid-19 Symptoms

Takeaways for Map 1: Districts in dark purple show where knowledge about how the virus spreads is lowest across districts. Respondents are scored from 0 to 3.  Note that a score of 1.5 is consistent with randomly guessing at the questions. True or false questions included: 1) Coronavirus can be spread through the air. 2) If someone has Coronavirus, they can spread it even before they show any symptoms. 3) There is a cure for Coronavirus.

Map 1: Mean score on knowledge about Coronavirus, by district

Willingness to Stay Home or Self-Isolate If Sick

Takeaways for Map 2: Districts in dark purple show where willingness to stay home or self-isolate if they have Coronavirus is the lowest. Districts overall report low willingness to stay home if sick, especially districts in the center and the south.

Map 2: Percent of respondents who say they would stay home or self-isolate if they have Coronavirus, by district

Willingness to Vaccinate

Takeaways for Map 3: Districts with the least willingness to vaccinate children for measles or polio are shown in dark purple. Unwillingness is widespread, but especially intense in the northwest.

Map 3: Percentage of all respondents reporting that they are unwilling to vaccinate their child for polio or measles, by district

Community Mobilization

Takeaways for Map 4 Districts in dark purple show where respondents reported the lowest percentage of active Covid-19 community groups. Community mobilization is low in most places, though there are a few scattered districts — Kambia, Falaba, Kailahun — that report relatively high community mobilization.

Map 4: Percentage of all respondents who report an active Covid-19 community group, by district

Implications for Lockdown Policies

Takeaways for Map 5: Districts in darker colors on the map below are least able to survive a lockdown of more than 3 days at a time would not work.  Almost all respondents in Port Loko and Pujehun fell into this category.  A cluster of districts in the northwest also had high numbers of respondents in this category.

Map 5: Percentage of all respondents reporting that they cannot survive a lockdown for more than 3 days, by district

Comparing Urban and Rural Capacity to Withstand a Lockdown

Note: The sample is roughly split between rural and urban respondents (53% rural; 47% urban). Though the sample size is small, post-stratification weighting with fine-grained census data can provide more precise analysis.

RURAL

Takeaways for Map 6 The map shows rural respondents, districts in dark purple are least able to survive a lockdown of 3 or more days. Rural respondents report higher vulnerability to lock downs.

Map 6: Percent of rural respondents who say the maximum they could endure lockdown is less than 3 days

URBAN

Takeaways for Map 7: The map shows urban respondents, districts in dark purple are least able to survive a lockdown of 3 or more days. 50% of rural respondents reported that a lockdown of more than 3 days at a time would not work. Note: Falaba District did not have any urban respondents for this study.

Map 7: Percent of urban respondents who say the maximum they could endure lockdown is less than 3 days

Food Insecurity

Takeaways for Map 8: Districts in dark purple have higher rates of food insecurity. Insecurity is distributed across the country, although a few districts in the south are less worrisome.

Map 8: Percentage of all respondents reporting that they had gone without food at some point in the last seven days, by district

Additional charts and results are available in the full report. For questions, please contact mitgovlab@mit.edu.

About

MIT Governance Lab (MIT GOV/LAB) is a group of political scientists focusing on innovation in citizen engagement and government responsiveness (https://mitgovlab.org/; mitgovlab@mit.edu].

Institute for Governance Reform [IGR] is an independent, multi-disciplinary, policy-oriented research team based in Sierra Leone (http://igrsl.org/; info@igrsl.org].

Directorate of Science, Technology and Innovation (DSTI) supports the Government of Sierra Leone to deliver on its national development plan effectively and efficiently; and to help transform Sierra Leone into an innovation and entrepreneurship hub (https://www.dsti.gov.sl/].

Ministry of Finance’s Research and Delivery Division (MoF-RDD) is mandated to formulate and implement sound economic policies and public financial management, ensure efficient allocation of public resources to promote stable economic growth and development [https://mof.gov.sl/].

Acknowledgments

Thank you to David Moinina Sengeh, Minister of Basic and Senior Secondary Education, Chief Innovation Officer, and Advisor to the President Republic of Sierra Leone; and Professor Osman Alimamy Sankoh, Sierra Leone’s Statistician General.

Thanks to Chenab Navalkha for data visualization and Daniel Tobin for data analysis support.