Unilag Housing Centre


Importance of Informal Household and Neighbourhood Level Data for Understanding the COVID-19 Pandemic and Building Responses in Nigeria




Peter Elias

Senior Lecturer & Lead, Lagos Urban Studies Group (LUSG), Department of Geography, University of Lagos, Nigeria



The COVID-19 pandemic has shown up in different patterns in different neighbourhoods in Nigeria. Understanding how it spreads, and how it can be mitigated in different kinds of neighbourhoods requires prioritizing neighbourhood-level data. This is even more pertinent because an estimated 70 percent of urban dwellers in sub-Saharan African, including Nigeria, live in slums and informal neighbourhoods[i]. These slum neighbourhoods are found in fragile and often undesirable neighbourhoods with potential to escalate or intensify COVID-19 in Nigeria. The neighbourhood context of place, activities, travel, socio-demographics, and behaviours are important pointers and bases for understanding and responding to the COVID-19 pandemics[ii].


Understanding the various ways in which COVID-19 affects different informal households and vulnerable slum neighbourhoods could form the basis for robust interventions towards local economic development. Informal households and vulnerable slum neighbourhoods depend on informal sector economy for their livelihoods. Leandro and collaborators[iii] have estimated that the livelihoods and incomes of informal households constitute about 80 percent of the national economy which account for 65 percent of gross domestic product (GDP) in Nigeria with a per capita GDP of $2,028. The COVID-19 pandemic has disrupted the informal economy which means that many informal households and slum neighbourhoods are bound to face acute disruptions[iv]. Several informal households who depend on daily paid jobs such as transport workers, street traders, artisans and craftsmen, farmers, fishermen, and hairdressers earn extremely low incomes cannot boast of savings and safety net. This could intensify the vulnerability of informal households and slum neighbourhoods to COVID-19.


There are various ways in which a neighbourhood can be conceptualized which may determine how to build location-specific responses to COVID-19. Neighbourhoods can be conceptualized spatially in which case the physical characteristics or attributes of places become the focus. Building responses to COVID-19 can benefit from spatial studies and technologies which make it possible to understand and map the spread and patterns at the neighbourhood level. In terms of functional conceptualization, neighbourhoods can evolve to serve specific functions which give them a unique character or an identity – residential, industrial, tourism, transportation or recreational or multifunctional – typical of many neighbourhoods in Nigerian cities. This multifunctional identity is a key element in neighbourhood evolution and complexity which could be challenging to building responses to COVID-19 in Nigeria. Neighbourhoods can also be conceptualized socially by understanding the cultural context and connections of the place which defines various social relations and capital as critical factors for building flexible responses.


In Nigeria, neighbourhoods differ one from the other in terms of size of the area, population, and density. The densely populated residential neighbourhoods including slums correspond to low-income communities, concentrated poverty, and lack of basic services. These indices of poverty and social disadvantages including poor road networks, absence of public water supply, inadequate sanitation among others, and could heighten the spread of COVID-19 and make building of responses difficult. Meanwhile, low-density neighbourhoods typified by the high-income Government Reserved Areas or Gated Residential Areas which epitomizes enhanced wealth or affluence, and better-quality services including underground electrical systems and water networks, uninterrupted electricity, adequate security, good road system, a central sewage system and treatment offer better advantages and could safeguard these neighbourhoods from COVID-19. Neighbourhoods also differ in terms of household characteristics, needs, deprivations, and assets which would also require context-specific interventions[v]. The divergent populations, demographics, or features of neighbourhoods in Nigeria might affect how COVID-19 spreads, or the kinds of data we might collect for evidence-based responses.


Meanwhile, when data is disaggregated at the household- and neighbourhood-level it becomes easy to match interventions with targeted places for sustainable solutions[vi]. Capturing data at the national level often masks evidence and limits sustainable solutions. For instance, understanding health behaviours and risk factors at the household or neighbourhood-level are strong ways of preventing or managing pandemics such as COVID-19. Also, data at the neighbourhood-level can help in identifying or tracing COVID-19 pandemics and the spread. There are emerging innovative techniques of using studies or mapping of open sewers in neighbourhoods to trace community-level COVID-19 infections[vii]. Using neighbourhood-level data for disease-mapping and trend analysis can enhance timely and accurate decision-making by individuals, communities, and nations. Solutions to COVID-19 pandemics become targeted at the neighbourhood-level rather than a chaotic and non-coherent approach at the national level because they pinpoint outbreaks and proffer place-based preventions and/or interventions.


Meanwhile, informal household- and neighbourhood-level data-collection has become a two-edged sword owing to obvious risks and challenges. Although such data help to link COVID-19 pandemics to places it can also result in unintended consequences such as stigmatization and evictions of slum dwellers and xenophobic attacks on other urban dwellers. For instance, since the outbreak of the COVID-19, several Chinatowns, businesses, restaurants, malls, casinos, in different neighbourhoods of the world major cities including Europe and America have suffered different degrees of discriminations[viii]. This means that data collected from informal households and neighbourhoods must follow stipulated guidelines and policies of data management and sharing. This should include anonymity and obscuring of identifying personal information to avoid unintended consequences.


There are many benefits of informal household- and neighbourhood-level data to build responses to COVID-19 pandemic despite the identified risks and challenges. First, it can be used to amplify the pathways and patterns COVID-19 in informal households and slum neighbourhoods of Nigeria[ix]. The data can be shared and visualized using various networks and platforms to draw attention to local status of COVID-19, available health facilities, assets, and local champions. It can also inspire self-organization and self-efficacy for empowerment and advocacy works towards improved household or neighbourhood hygiene. Second, disaggregated data by individual, household and community can make interventions and solutions more targeted such as interventions to empower widows, single mothers, or female-headed households to build sustainable livelihoods amid COVID-19. Third, there is a possibility of co-design and co-production by engaging multiple stakeholders and linking local COVID-19 situations to solutions at the national and global levels. This can strengthen the application of transdisciplinary research which brings together scientific and non-scientific communities to tackle COVID-19 pandemic in Nigeria. For instance, the academic researcher brings information about the pathways and patterns of COVID-19 to connect with community knowledge on the use of local folklores to disseminate the information. Or it can connect local actors with state actors to instill appropriate health guidelines or protocols for handwashing, physical or social distancing and self-isolation. Through this symbiotic relationship suitable interventions can be co-designed and co-produced using a participatory model grounded at the community level. This can increase the chance of reception, adoption, and application at the local level. It ultimately leads to savings in costs of COVID-19 intervention design, aligns with local contexts, and safeguards commitment of residents to building responses which is highly localized using informal household- and slum neighbourhood-level data.


[i] World Data Atlas (2019) Nigeria – Urban population as a share of total population

https://knoema.com/atlas/Nigeria/Urban-population and United Nations DESA (2018) Revision of World Urbanization Prospects. A publication of the Department of Economic and Social Affairs.

[ii]  Agoada, Joseph (2012) Data Points as Change Agents: Lessons from UNICEF–GIS development

A UNICEF Special Presentation to the Worldwide Human Geography Data Working Group

[iii] Leandro Medina, Andrew Jonelis, and Mehmet Cangul (2017) The Informal Economy in Sub-Saharan Africa: Size and Determinants. Working Paper, International Monetary Fund

[iv]  See my recent article: Elias, Peter (2020) Why Nigeria’s efforts to support poor people fail, and what can be done about it. The Conversation Africa. https://theconversation.com/why-nigerias-efforts-to-support-poor-people-fail-and-what-can-be-done-about-it-137122

[v] See my previous work: Elias, Peter, Mayowa Fasona Olatunji Babatola, & Ademola Omojola, (2017) Prioritising Community Needs Assessments and Strategies for Sustainable Urban Service Delivery and Governance: Case Study of Lagos Slum Settlements Unilag Journal of Humanities. Vol.5,No.1 pp.25-48

[vi] United Nations DESA (2020) Better disaggregated data to assess the implications of COVID-19 on women and men

[vii] Liu, Lu (2020). Emerging study on the transmission of the Novel Coronavirus (COVID-19) from urban perspective: Evidence from China. Cities, vol. 103

[viii] Eric Olander (2020) Chinese in Kenya Face Stigmatization and Discrimination Due to COVID-19

https://chinaafricaproject.com/2020/03/03/chinese-in-kenya-face-stigmatization-and-discrimination-due-to-covid-19/ The Africa China Project, March 3, 2020; and Knowles, Hannah and   Bellware, Kim (2020). Fear sent her Chinatown restaurant spiralling.  The challenges to reopening feel ‘just impossible.’

The Washington Post, March 16, 2020.

https://www.washingtonpost.com/nation/2020/05/16/asian-american-business-coronavirus/; and Konstantinides, Anneta (2020) An NYC Michelin-starred restaurant was vandalized with racist graffiti as attacks against Asian-American workers are on the rise. https://www.insider.com/racist-graffiti-new-york-city-restaurant-during-coronavirus-2020-4 Insider, April 17, 2020

[ix] United Nations (2014) Voices from Slums. World Habitat Day


No 11 – This blog article is written under the auspices of the British Academy supported Critical Thinking and Writing Workshop for Urban Studies Researchers in Nigeria.


The views expressed in this article are those of the author(s) and not necessarily those of the Centre for Housing and Sustainable Development or the University of Lagos, Nigeria.