Trends in the size of the elderly population in Africa

 There is a significant variation in the trend of the ageing population across sub-regions (Figure 1). North Africa has exhibited rapidly growing ageing population driven both by improved life expectancy and reduced fertility rates[2], followed by Southern Africa. There is near stagnancy of the share of the ageing population in West and Central Africa, partly contributing to the slow demographic transition witnessed in Africa. Such variations in the ageing population across sub-regions and countries in Africa suggest differences in underlying health systems, formal and informal care systems, and social protection programs.

Figure 1: Growth of the elderly population by sub region in Africa

Source: author’s computations based on data from UNFPA

The profile of the ageing population in Africa.

• The ageing population tend to be higher in rural than urban areas in Africa despite exhibiting better life-expectancy, low fertility rates, and relatively better infrastructure.
• Proportion of women elderly is higher than their male counterparts in both rural and urban areas.
• The proportion of the elderly active in the labour market tend to be high in Africa, particularly in Sub Saharan Africa. The labour market participation rate of the elderly in comparison to the participation rate of the work force (15-64) is above 65% for all regions, except North Africa, where this share is less than 40%.
• The variation in the size of the ageing population between African countries could be explained by differences in the level of economic development achieved, life-expectancy at birth attained, and social policies such as public spending on health, social insurance coverage, social contributions, and interpersonal transfers (remittances).
• Key indicators associated with the variations in the size of the ageing population include life expectancy at birth, per capita GDP, labour force mobility and social policies (Table 1).

 Table 1: Factors correlated with the ageing population in Africa

Note: *significant at 5% p-value.

Source: author’s computations based on data from UNFPA and WDI

•   Elderly heads of households exhibit higher deprivation rates than the non-elderly in Africa. They tend to have poor access to safe drinking water, sanitation, live in badly constructed houses, exhibit higher degree of malnutrition, and lack access to information (Table 2).

 Table 2: Correlation between old (65+) household heads and access to basic social services: 1980-2018

 Source: author’s computations based on DHS data
 Figure 1: Asset poverty (headcount ratio) is more prevalent among the old-age population in Africa

Source: author’s computations based on DHS data

Note: Figure 1 plots by country the proportion of old-age head of households that are asset-poor in comparison with younger age group. The figure is based on computations from DHS data averaged over the period 2000-2018

• The proportion of the asset-poor among the elderly was much higher than those relatively younger households suggesting that the elderly in Africa tend to suffer significantly from lack of basic social services and material needs (Figure 1). However, the degree of deprivation varies considerably across countries, where the proportion of the asset poor tended to be relatively higher in some countries such as Zimbabwe and Zambia relative to the non-elderlies, while the difference is negligible in Central African Republic, Egypt, Nigeria, etc. (Figure 2).
• 24 out of 37 countries asset poverty trended to be higher among the elderly women than elderly men. Such significant gender difference is pronounced in Angola, Zambia, Zimbabwe, and Democratic Republic of Congo. Hence, closing the gender gap alone can contribute significantly to reducing deprivation among the elderly in Africa.

Figure 2: Asset poverty (headcount ratio) between male and female headed elderlies

Source: author’s computations based on DHS data

•  In conclusion, the ageing population has been increasing both in relative and absolute terms in Africa due to several factors, including improvements in life-expectancy, better economic conditions, changes in fertility rates and implementation of social policies that favour the elderly population.
• Still, poverty and deprivations tend to be more pronounced among the elderly in Africa. Evidence from asset-based poverty indicate that the proportion of elderlies that lacked access to basic services such as safe drinking water, electricity, decent housing, and nutrition tend to be high in all Africa countries suggesting the need for greater effort and policy coordination to implement robust social protection programs.

[1] Author’s computations based on data from UNFPA (2021): https://population.un.org/wpp/

[2]  North Africa has the highest migration rates in Africa potentially contributing to the rising share of the elderly population. See https://www.migrationdataportal.org/regional-data-overview/northern-africa

This brief is based on the author’s contribution to a policy paper “Policy Brief on Ageing, Social Protection, and Covid-19 pandemic in Africa”, September 2021, Gender, Poverty and Social Policy  Division, UNECA

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The task of instituting a functioning social security programs, targeted social protections and well-defined basic health facilities for the elderly remain a big challenge. Below I provide some suggestive evidence on common indicators used to capture social policies for the ageing population. These are share of social contributions to total government revenue. This indicator provides information on the share of contributions made directly by employees (for example civil servants, employees of state-owned enterprises, etc.) or on their behalf by public or private companies depending on the type of pension schemes. The global average is around 8.3%[1] in 2019, while for Africa it was 4.8% with considerable variation across countries.

Figure 1 reports a strong and positive association between social contributions as a share of total government revenue and the size of the elderly population in Africa. Countries that tended to expand social contributions (pension schemes, unemployment benefits, etc.,) seem to have gained through improved life-expectancy, hence higher size of the elderly population.

Figure 1: Proportion of the ageing population and social contribution as a share of revenue

Source: author’s computations. Note: the graph plots social contributions as a share of total government revenue averaged over the period 1990-2020 against the proportion of the ageing population among African countries.

• While middle income countries such as Mauritius, Seychelles, and Tunisia tended to have high social contributions as well as high proportion of the ageing population, countries such as Botswana, Morocco and South Africa have low social contribution rate yet relatively high proportion of ageing population indicating the potential role of per capita GDP in improving life expectancy.
• Whereas countries such as Angola with comparable per capita GDP and social contributions as that of Botswana recorded low proportion of the ageing population which indicates the complexity in understanding the drivers of the ageing population.

Figure 2 complements the role social policy plays in improving the size of the elderly population by mapping the share of the population covered under social insurance with the size of the elderly population, showing a strong positive association. Countries such as Egypt and Ghana lead by providing social insurance for over 20% of their population which is the highest coverage in Africa. Nearly all other African countries had only a fraction of the population had access to social insurance.

Figure 2: Proportion of the ageing and social insurance coverage in Africa

Source: author’s computations based on World Development Indicators (various editions)

Note: The graph plots average values of social insurance coverage as percentage[2] of population with respect to the proportion of the ageing population for the period 1990-2020.

While few countries have implemented alternative pension systems to care for the elderly, it is also possible to argue that the ageing population benefited from basic social services provided by governments that improved welfare. To examine the association between social policies and the ageing population, Figure 3 displays a diagram between life-expectancy (proxy for better care for the elderly population) and social contributions after accounting for differences in the level of

development (or per capita GDP). The relationship as shown is strong and indicative of the influence of social policies on welfare of the elderly population in Africa.

Figure 3: Bin-scattered diagram of life-expectancy and social contributions in Africa

Source: author’s computations.

The relationship between ageing population and social policies (social contributions and social insurance coverage) is mediated through life-expectancy. Countries that run a very good social programs (like social contributions and insurance) tend to register better life-expectancy after controlling for differences in the level of development (per capita GDP). The same relationship holds between public spending on health as a share of GDP and the welfare of the elderly.

In conclusion, even though social policies targeting the care of the elderly are at a formative stage in many African countries, the existing programs seem to have some degree of positive effect on the welfare of the elderly as discussed above. More research is needed to see if the pension schemes and other social benefits, such as health care are commensurate with the size of social contributions and social insurance schemes so that reforms can be implemented to improve the caring for the elderly. In this regard, Africa also has a huge potential in rolling out better social policies for the ageing population as the structure of its economy improves over time. Figure 4 below shows that

there is strong and negative association between share of the labor force in the informal sector and the share of the ageing population suggesting the possibility that in the long-term more contributory pension schemes could evolve in Africa.

Figure 4: Informality and the ageing population in Africa

Source: author’s computations based on data from UNFPA (2021) and ILO (2020)

[1] See https://data.worldbank.org/indicator/GC.REV.SOCL.ZS

[2] According to the World Bank (https://datacatalog.worldbank.org/coverage-social-insurance-programs-population-0) the data on the percentage of the population with social insurance is defined as follows ”Coverage of social insurance programs shows the percentage of population participating in programs that provide old age contributory pensions (including survivors and disability) and social security and health insurance benefits (including occupational injury benefits, paid sick leave, maternity and other social insurance). Estimates include both direct and indirect beneficiaries

This brief is based on the author’s contribution to a policy paper “Policy Brief on Ageing, Social Protection, and Covid-19 pandemic in Africa”, September 2021, Gender, Poverty and Social Policy  Division, UNECA

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This brief presents evidence based on high frequency data on the impact the COVID-19 pandemic had on emotional and psychosocial well being in Kenya mainly during the period March 2020-October 2020. Table 1 suggests that at the height of the pandemic (May 2020) when most governments in Africa declared lock downs and state of emergency, the percentage of households that suffered from elevated anxiety reached to 75%. As people begun to get better information on the spread of the virus, anxiety levels seem to have decreased. Still the proportion of the population suffering from serious anxiety during the pandemic exceeded 50%. A major factor driving heightened anxiety seems to be the fear of contracting the virus. Throughout the period under study, the proportion of households who felt anxious of contracting the virus hovered around 80% with no change in the trend. It is clear also from the table that while economic activity declined following the lock downs around May/July 2020, the fear of losing jobs loomed large in 2021 suggesting the gradual erosion of livelihoods in the wake of the pandemic and lack of job security and social protection.

Table 1. Incidence of Anxiety and emotional stress in Kenya: 2020/2021

Source: authors’ computations.

• Table 1 described the trend in the degree of anxiety and mental distress in the general population. It may also be interesting to know who suffered most during this period and what important factors seem to be correlated with anxiety levels in the population?
• Table 2 suggests that anxiety levels seem to be much higher among women indicating the disproportionate burden falling on women during such shocks, in terms of taking care of the family as well as fighting the disease. According to table 2, on the average, women tended to exhibit 10% higher anxiety levels than men.
• The other important factor associated with anxiety levels is age where younger household heads exhibited relatively higher levels of anxiety compared with older ones.
• The other revealing factor associated with anxiety levels is the perceptions households have towards their government. Households that had no trust at all on government or feel indifferent about its trustworthiness suffered a significantly higher anxiety levels (52% and 72%, respectively) than those who tended to trust the government.
• This is suggestive of the underlying causes of anxiety resting on the perceived information gap as well as mistrust on the information shared by government authorities about the pandemic.

Table 2. Marginal effects from a probit model regression for Kenyan household survey.

Source: authors’ computations. Note: Z statistics in parentheses * p<0.05, ** p<0.01, *** p<0.001

Related to anxiety, the pandemic such as this created the conditions for stereotyping, discriminations and stigma towards others perceived to be contracting the disease. During the pandemic, stigma is described as the one virus that is spreading even faster than the COVID-19 Pandemic[i]. The disease is new with very little-known information causing fear, panic, and misinformation. The fear of disclosing having the virus to others has   brought a sense of shame in the society and created stigmatization. For fear of being stigmatized or marginalized, people tend not to disclose their status about the virus even to close family members by failing to get tested. The shame associated with disclosing of having the virus has led to substantial psychological distress, which doesn’t end there but the person infected with the virus continues transmitting the disease knowingly to the community without being tested. This cycle of fear of being infected by the virus, associated with the shame and stigmatization, coupled with economic and social uncertainties has led to a high level of mental distress among communities.

Table 3 below reports that women tend to be less stigmatizing than men (by nearly 8%) and generally the level of stigma started to decline as the virus continued to affect a large percentage of the population.

Table 3. Probit model regression on factors correlated with negative perceptions of people with COVID-19

Source: authors’ computations. Note: Z-statistics in parentheses * p<0.05, ** p<0.01, *** p<0.001

Finally, the measures taken by authorities to stem the spread of the virus such as stay-at home orders, school-closing policy, public-gathering restrictions, cancellation of public events has led to enormous psychological distress and uncertainties for many people. It has also created opportunities for heightened violence such as domestic violence, gender violence, spouse violence, sibling’s violence. Table 4 reports that areas under severe lockdown had 26% higher rates of violence in Kenya suggesting the strong association between lockdowns and violence.

Table 4. Incidents of lockdown related violence

Source: authors’ computations. Note: Z statistics in parentheses * p<0.05, ** p<0.01, *** p<0.00

In conclusion, mental health problems got worse as a direct consequence of the COVID 19, and because of job losses and loss of economic opportunities. While loss of jobs tends to be temporary, some jobs may not be back. There is need to empower those that have lost jobs so that they manage the transition in these difficult times. Unfortunately, most interventions to fight the pandemic do not include mental health care despite growing evidence on the people suffering from anxiety, depression, stigma, and violence. Grassroots institutions including schools, universities, and media houses should be empowered to offer mental health care to reach the general population. Lessons should be taken on long term impact on mental health and stigma from past pandemics like HIV /AIDS and Ebola.

[1] .  (https://www.worldometers.info/coronavirus/#countries, Nov 2021).

[2] Josephson, A., Kilic, T. & Michler, J.D. Socioeconomic impacts of COVID-19 in low-income countries. Nat Hum Behav 5, 557–565 (2021). https://doi.org/10.1038/s41562-021-01096-7

[3]  Pfefferbaum et al (2020)https://www.nejm.org/doi/full/10.1056/nejmp2008017

[i]  (Kim Robin van Daalen, 2021)

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The elderly generally faced either similar or higher loss in income, and experienced reduction in food consumption as a result. For instance, over 60% of the elderly in Chad, Mali, Malawi Nigeria and Uganda suffered income loss as a result of the pandemic, and same percentage also reduced food consumption, risking hunger (Table 1). In addition, most elderly received higher remittances from families and friends to cope with the challenges posed by the Covid-19 pandemic. This could have been the situation even prior to the pandemic noting that cash transfers whether from individuals or governments (as in the case of South Africa) tend to go from the younger to the older generation. Still despite efforts made through cash transfers to help the elderly, it is shocking to note that significant proportion of the elderly had to reduce food consumption to cope with the pandemic.

Table 1: Income loss, reduction in food consumption and social support among the ageing population during Covid-19 pandemic

Note: The table reports results from high frequency household surveys conducted over a telephone. * is direct transfer from government, **Computation for Nigeria to be completed

Source: author’s computation based on high frequency household survey data (World Bank)

The elderly in Africa continued to be active in the labor market despite their age as shown in Table 2. The pandemic hence affected their job prospects at almost equal measures as other age groups This has caused most elderlies to suffer from income losses in almost comparable degree. For instance, in Mali, Malawi and Nigeria, the income loss and subsequently the food shortage has been comparable with the non-elderly.

Table 2: Job loss by the elderly as a result of Covid-19 pandemic in Africa

Source: author’s computation based on high frequency household survey data (World Bank)

This brief is based on the author’s contribution to a policy paper “Policy Brief on Ageing, Social Protection, and Covid-19 pandemic in Africa”, September 2021, Gender, Poverty and Social Policy  Division, UNECA

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It is generally acknowledged that urbanization is often accompanied by modernization of an economy, concentration of social organization, rising incomes, and improved living conditions, etc.[1]. This common trend however may not materialize in all cases. The experience of Africa is a case in point a continent where urbanization is taking place at a faster rate than anywhere else in the globe.

In the last two decades, the share of the population living in urban areas increased from about 30% in 1990 to approximately 47 percent in 2020. This has led to increased rural-urban migration impacting urban population growth and slum proliferation in Africa. This brief focuses mainly on urbanization, slums, and poverty in Africa.

Figure 1: Trends in urbanization in Africa

Source: author’s computations based on data from World Development Indicators various editions.

Urbanization and slums in Africa

One of the untended consequences of rapid urbanization in Africa is the proliferation of slums where living conditions are characterized by overcrowded and unsanitary houses made of plastics, no toilet facility, and other amenities, including little or no access to basic social services such as electricity, schools, health centres and others, and infested with criminal activities, widespread substance abuse and lawlessness. The question remains is it urbanization per se that led to slum growth in Africa, or are there other underlying structural and policy factors? A cursory look at the data suggests that the size of the population living in slums declines with urbanization (Figure2). It also indicates that the size of the population living in slums is as widely prevalent in less urbanized countries as those in more urbanized ones which is worrisome. There are thus some common policy failures and structural impediments that enabled the proliferation of slums in Africa.

Figure 2: Urbanization and prevalence of slums in Africa

Source: author’s computations based on data from World Development Indicators various editions.

To get slightly a better sense of how rapid urbanization could facilitate the prevalence of the population living in slums, Figure 3 controls for variations in per capita GDP across countries which is an important structural or developmental factor that could be associated with the pace of urbanization. The results suggest that more urbanization in Africa could lead to the proliferation of slums in Africa.

Figure 3: Urbanization and slums controlling for differences in per capita GDP

Source: author’s computations based on data from World Development Indicators various editions.

One of the reasons often cited for the proliferation of slums in Africa is rapid growth in internal migration from the rural to urban areas. Among the many concerns are the creation of slums in the cities, poverty, unemployment, and rising crime. In most African cities, basic infrastructures are not set up or met up with the standards to accommodate more people than it is supposed to. As a result, most cities in Africa are overpopulated, the bulk of which reside in an overpopulated environment having to set up plastic and tent houses that turns the cities into slums. This is a big concern and raises a serious challenge for policymakers.

 Slums and poverty in Africa

The defining characteristics of slums is the human suffering they entail and the challenge they create in perpetuating inequalities in close neighborhoods and terrible living conditions that undignified humanity. The evidence for Africa is telling. Figure 4 presents the association between the share of population living at poverty line of 3.12 USD in PPP per person per day with the share of population living in slums in Africa. This is in sharp contrast with the association between urbanization and poverty in Africa which is negatively correlated (see Annex Figure 1).

Figure 4: Slums and poverty in Africa

Source: author’s computations based on data from World Development Indicators various editions.

 The association between slum proliferation and poverty persists even when we control for differences between countries in the level of per capita GDP which is an important determinants of poverty conditions. This suggests that irrespective of the level of development, slums continue to be characterized by prevalence of extreme poverty (Figure 5).

 Figure 5: Slums and poverty in Africa controlling for differences in per capita GDP

Source: author’s computations based on data from World Development Indicators various editions.

 Africa’s fight against poverty is challenged by prevalence and continued growth of the population that lives in slums across the continent. The following section outlines these challenges and policy options.

The challenges associated with slums in the urbanization process

Urban planning and management are key development challenges. Urbanization needs well-designed, inclusive, and targeted policies at all levels. The challenges are as follows.

• Failure to put a socio-economic development plan in rural areas could enhance migration to urban cities. The very reason for migrating to the cities are the rapidly declining agricultural activity in rural areas and not having to put an alternate development plan for those no more engaging in the agriculture sectors has been the main challenges. Mostly, the informal sector in urban areas is linked with the rural sector that encouraged unskilled laborers to escape from rural poverty and underemployment, granting them living and working conditions that do not bring substantial incomes to sustain them living in the cities. Despite the developmental challenges associated with migration and urban growth in Africa, migrants contribute to the nation’s socio-economic development. However, this needs careful planning and policy development by the governments of African policymakers.
• Failure to mitigate the growth of slums in informal settlements is an important aspect of Africa’s development challenges. Although population growth and accelerated rural-to-urban migration are chiefly responsible for expanding urban shantytowns, part of the blame rests with the policymakers. Most of these settlements lack clean water, sewage systems, and electricity. In addition to the lack of basic infrastructure, the rapid growth of slums has aided in breeding poverty, crime, social tension, and pollution.
• Failure to have a proper urbanization plan in the cities has also led to weak infrastructure development. These have led to many challenges such as limited job creation, inadequate structural transformation, poor liveability, poverty, health, environmental quality, and social welfare provision. It has also led to the urban poor and the expansion of informal self-employment.

The way forward

It is undeniable that migration has a dual effect on development, in which the formal sector depends on the informal and vice versa. Nevertheless, there is a need to harmonize the two, rural-urban migration and development of both sectors. African urban population will continue to grow, with rural-urban migration continuing to drive the urbanization process. Africa needs a sustainable urbanization plan driven by the concentration of investment and employment opportunities in both urban and rural areas that secures a tenure to improve access to economic opportunity, including livelihoods, public and municipal services. For an urban development plan to be successful, it needs to boost economic growth where cities can create jobs and offer better livelihoods, improve social inclusion, reduce both urban and rural poverty. Due to the low level of GDP in Africa, lack of adequate resources and inadequate investments such as public and private investments in housing, infrastructure, and other capital is lacking. Moreover, limited land management and lack of infrastructure contribute to African cities being fragmented, with low accessibility to jobs and social services[2]. In conclusion, Africa needs to work more on an effective policy framework incorporating migration into sustainable urban-rural development programs that remained the greatest challenge.

Annex Figure 1: Urbanization and poverty in Africa

[1] See Kudus et al (2020) https://publichealthreviews.biomedcentral.com/articles/10.1186/s40985-019-0116-0

[2] Urban economic growth in Africa: A framework for analyzing constraints to agglomeration. ( John Page, Jeffrey Gutman, Payce Madden, and Dhruv Gandhi. 2020.)

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Once WHO declared COVID-19 a pandemic, many African countries heeded the guidelines provided by WHO in tackling the spread of the SARS-2 virus. The major guidelines included a) restrictions of mobility of people, within and between countries; b) restrictions of large gatherings, including weddings, funerals, rallies, sport games, church services, etc., to enforce social distancing; c) closure of offices, schools, businesses to avoid flareups, d) increase testing and tracing; e) handwashing and wearing of masks, etc. Some institutions, such as the Oxford University developed the Stringency Index to capture how countries have been coping with the COVID-19 pandemic since it all begun in around February 2020[1]. As can be seen in Figure 1, Stringency Index for Africa started climbing very sharply around February 2020, reached its peak sometime in 1^st of July 2020 and started declining slowly until October 2020. Most countries started relaxing movements after November but reintroduced stringency measures in the wake of new wave of COVID-19 spread. This brief addresses the following questions? How effective have been stringency index in stemming the COVID-19 pandemic? Given the enormous disruptions in livelihoods, were African governments sufficiently prepared to provide buffers to vulnerable households? What should be the priority in the post-COVID-19 world for African governments?

Figure 1: Mean daily trends in stringency index and mobility of people to retails stores in Africa

Source: author’s computations based on data on Stringency Index and Google mobility data
(https://www.google.com/covid19/mobility/ ) in 54 African countries

Has stringency worked in containing infections?

There are credible reasons to think that the WHO guidelines to combat the spread of the virus causing COVID-19 outlined above would work in a setting where living conditions are such that people have access to private living rooms, which helps to isolate infected people; running water in all rooms; access to information (telephone, TV, and other information media); and other amenities. Data from Demographic and Health Surveys for African countries show that most people do not have access to radio, TV, electricity, sufficiently spaced rooms, etc. (Table 1). In this situation, it is very difficult to expect the stringency measures to make much headway in controlling the pandemic.

Figure 2 echo these limitations in the context of Africa despite measurement errors in the rate of daily infections which at the initial period focused only on people showing some symptoms as testing capacity was very low. Around April, testing capacity improved significantly in most African countries which was also correlated highly with the stringency index. However, even after April 2020, daily infection rates climbed steadily, while stringency index declined only slightly. The correlation coefficient between infection rates and stringency index was only 12% quite very low. In this regard, stringency measures impacted infection rates quite marginally. One of the lessons learned is therefore how to make stringency measures effective in case such future incidents happen. This include the preparation of the health care system to manage pandemics/epidemics, sensible use of key protective measures, such as masks and sanitizers, educating people on social distancing; sheltering vulnerable groups (the old, the sick and others) in areas where they could be protected from the public, etc.

Figure 2: Stringency index and daily infection rates

Source: author’s computation based on data described above.

Governments could harness the lessons from COVID-19 pandemic to help vulnerable households on a sustainable basis.

The economic consequences of the pandemic have been very well documented. Millions of Africans lost jobs, income, and experienced significant livelihood shocks. Unfortunately, there are no well-designed and functioning social protection programs in Africa that could be invoked at such a time as this. As a result, poverty increased sharply in many countries leading also in some cases to malnourished. Can African governments afford to institute and implement effective social protection programs to fight poverty, provide health care and other basic needs, such as education? A cursory look at the basic statistics and potential of the African economy suggest that it is indeed possible to promote social inclusion and address inequity by blending formal and informal social assistance programs. According to the World Bank, the magnitude of extreme poverty (percent of the population living below the poverty line of 1.9 USD in PPP per person per day) was 34%[2]. The poverty gap, which measures average shortfall of the income of the poor from the poverty line, was 12.7%. Combining the two, it would take 14% of Africa’s GDP transferred to the poor every year to eliminate extreme poverty. Certainly, faster economic growth would help to lift poor households out of poverty on a sustainable basis, but it is not sufficient. Some degree of complementary income transfer, even for the working population may be needed through various social protection programs. This may involve community participation, faith-based organizations, self-help organizations, etc. which could be leveraged to institute a functioning and efficient social protection program. The COVID-19 pandemic revealed the potentials of these institutions. Surveys across Africa showed that interpersonal transfers by friends, relatives, family members, self-help organizations, and others provided substantial assistance to the neediest at the height of the lockdowns. This lesson could be harnessed to fight poverty on a sustainable basis using local knowledge, community organizations and government support.

• Evidence from high frequency panel data in several African countries showed lockdowns and other stringency measures led many households to experience hardships
• The Covid-19 pandemic has led to significant disruptions in livelihoods, affected material and emotional wellbeing as well as caused social unrest.
• There have been contractions in economic activities, rise in unemployment, loss of incomes that led millions of households to cut down on their food consumption, miss meals for prolonged period and suffer from emotional distress and anxiety.
• The rise in unemployment in several African countries during the lockdown was unprecedented. Nearly all sectors of employment were affected, evidently some more than others.
• The pandemic has shown also how little trust people have on their government, a critical issue to build a community-government partnership.

What should be the priority for post-COVID-19 recovery in Africa?

• Could African governments have done differently in managing the pandemic?
• How fast recovery could be restored in employment? Which sectors of employment could generate rapid recovery and which ones could lead to permanent job losses?
• What would be the future role of well-designed social protection programs in a situation such as this?
• What would be the potential for community-government partnerships to fight such shocks?
• How could governments protect vulnerable groups, mainly women and children?
• The policy responses particularly lockdowns have led to a significant economic and social disruptions. The evidence on the effectiveness of the lockdowns in containing infection rates was little and at best not strong.
• Governments could learn from this experience in managing future pandemics by implementing smart containment policies that depend on the epidemiological characteristics of a pandemic while maintaining the economy running.

Policy Implications

African governments may not be able to sustain and enforce lockdowns for a period long enough to contain a pandemic considering the huge burden falling on households and the ensuing psychosocial problem it creates (violence, anxiety, and mistrust)

Smart policies require:

• Ensuring readiness of the healthcare system to track, isolate and treat infected persons
• Implementing preventive measures (such as community understanding of the transmission mechanisms, availability of masks and sanitizing materials at affordable prices) with diligence
• Keeping people vulnerable to the virus under special care
• Recovery from the pandemic is a long road ahead for many countries. The challenge is to know the full impact of the pandemic on household wellbeing. Few countries have the necessary information to identify the social groups that carried the burden of dealing with the pandemic.
• Despite the challenges, the pandemic also offers an opportunity to implement innovative social protection programs that target well the vulnerable groups through community-government partnerships.

[1] See the full details of the Stringency Index in Hale, Thomas, Jessica Anania, Noam Angrist, Thomas Boby, Emily Cameron-Blake, Martina Di Folco, Lucy Ellen, Rafael Goldszmidt, Laura Hallas, Beatriz Kira, Maria Luciano, Saptarshi Majumdar, Radhika Nagesh, Anna Petherick, Toby Phillips, Helen Tatlow, Samuel Webster, Andrew Wood, Yuxi Zhang, “Variation in Government Responses to COVID-19” Version 12.0. Blavatnik School of Government Working Paper. 11 June 2021. Available: www.bsg.ox.ac.uk/covidtracker

[2] See the aggregate poverty computed from Povcalnet (http://iresearch.worldbank.org/PovcalNet/povOnDemand.aspx)

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The share of the urban population in Africa grew from about 32% in 1990 to about 47% in 2020. Such phenomenal growth is expected to be either caused or led by a process of modernization or industrialization. Most observers and researchers suggest that urbanization in Africa has followed a rather different path where urban settlements have been characterized generally by a movement of people from agrarian subsistence framing to be employed in the equally less productive, informal sector with little industrialization taking place[1]. Part of the dynamics explaining this phenomenon is the preponderance of push factors in rural areas, such as landlessness, population pressure, conflict) than pull factors in urban areas (high remunerative job opportunities, etc). This may be true in a number of cases. But this is not also the full picture. In fact, it could be an oversimplification. This brief examines the association between urbanization and employment in the modern sector using highly dis aggregated GDP and employment data (10-sector)[2] for 11 African countries covering the period 1985-2012.

Figure 1: Urbanization and share of employment in manufacturing (%)

Note: Author’s computations based on data by Timmer et al (2015)

Figure 1 shows that during 1985-2012 urbanization in Africa was associated with high rate of employment in the manufacturing sector. This is a pattern slightly different from the established narrative that urbanization took place in Africa with little or no process of modernization in the economy. It is important to note also that there is relatively high degree of variation in the experiences of countries around the mean (linear regression line). There are countries where urbanization rate is between 30-45% yet share of employment in the manufacturing sector is less than 5% and vice versa. From Figure 1 it can also be argued that even for countries where urbanization exceeded 50%, employment in the manufacturing sector did not exceed 15%, hence compared with other regions of the world, African urbanization is still not dominated by a process of industrialization.

Figure 2: Share of urban population and valued added in manufacturing in Africa

Figure 2 also illustrates similar patterns on the association between urbanization and modernization rates in Africa where the share valued added in the manufacturing sector was positively and  strongly correlated with the rate of urbanization. While Figures 1 and 2 provide relationships that may be of long-term nature between urbanization and modernization of the economy, where underlying structural and institutional differences between countries could be at a play, Figure 3 presents the growth rates in urbanization and that of employment in the manufacturing sector, which underpins more of the instantaneous relationships. It is shown that countries that experienced higher pace of urbanization also experienced higher rate of growth in employment in the manufacturing sector strengthening the argument that urbanization in Africa did not take in a vacuum of economic transformation.

Figure 3: Growth in manufacturing employment and rate of urbanization in Africa

During this period, on the average urbanization grew in these countries at a pace of around 2.8% per year, while employment in the manufacturing sector grew at around 2.5%. From Figure 3 it could be inferred that a 1% growth in urbanization led to a 1.2% growth in manufacturing employment which is quite substantial.

Poverty declined in countries with high rate of urbanization, but inequality also worsened

One of the positive effects of urbanization in Africa is that it has led to significant decline in the rate of poverty between countries. Hence it is conceivable to expect that the process of urbanization, particularly one that is underpinned by modernization of the economy could be important to tackle poverty in Africa. Estimate of the elasticity of poverty with respect to urbanization suggest that a 1% increase in the pace of urbanization could yield a poverty reduction rate of 1.2% per annum. Given that urbanization on the average in the countries in our sample increased at a pace of around 2.8%, we would expect poverty to decline by around 3.6% annually. It is also important to note the country variations where this reality may not happen. There are countries where urbanization rate is over 40%, yet the percentage of the population living in poverty is higher than 50%. Fleshing out the factors underpinning such heterogeneous experience becomes very important for policy purposes.

Figure 4: Extreme poverty and urbanization in Africa

Finally, all is not rosy in the urbanization process. As Figure 5 shows it is also a process that is not equalizing. The Gini coefficient, popular measure of economic inequality suggest that it is positively correlated with rate of urbanization. Countries that have high rate of urbanization also exhibit high degree of inequality. This may not be surprising as urban economies are more differentiated and exhibit livelihoods with varying earning differentials compared with those in rural areas. As countries urbanize, they will be facing serious and persistent inequality that could be harmful for political stability and future progress in economic activities.

Figure 5: Inequality and urbanization in Africa

In summary, this brief presented a few facts about some features of urbanization in Africa. While the dominant narrative remains where still most African cities are crowded and are host to millions of people surviving on minimum earnings or wages mostly in the informal services sector, there has been also a positive trend that has been little noticed taking place. One of these is that manufacturing employment, both in levels and rate of growth has been positively correlated with the pace of urbanization. In addition, countries that tended to have high urbanization rates also exhibited low poverty rates. We have also noticed that some of the most urbanized countries (with urbanization rates above 50%) exhibited inequality levels that are pervasive reaching more than 40% and in some cases above 60% rendering the prospect of urbanization to be un-equalizing in the development process. There is some hope when it comes to poverty and inequality in the urbanization process. The relationship does not hold when growth rates are taken, indicating that the pattern documented in Figure 4 and 5 is more of a long-term relationship driven by structural and institutional factors prevailing in the continent. More research is needed to drill down how public policies could shape the urbanization process to become friendly to inclusive growth going forward.

[1] E.g see Potts, D. “Challenging the Myths of Urban Dynamics in Sub-Saharan Africa: The Evidence from Nigeria”, World Development” vol 40, no 7, pp 382–1393,

[2] The data source is Timmer, M. P., de Vries, G. J., & de Vries, K. (2015). “Patterns of Structural Change in Developing Countries.” . In J. Weiss, & M. Tribe (Eds.), Routledge Handbook of Industry and Development. (pp. 65-83). Routledge.

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As part of the fight to contain the spread of the COVID-19 pandemic, almost all countries around the globe responded by initiating confinement measures, including restriction in travel, partial and full lockdowns.

These measures led to the loss of jobs and disruption in incomes. The suffering was most severe in developing countries where the majority earn their living from self-employment and informal jobs, which to begin with was no better than starvation level with no fallbacks. The lockdown took a toll particularly on women who generally had to struggle to put food on the table for a large household, while contending with idle husbands who had never used to stay at home for extended periods.  There has been a sharp increase in intimate partner violence, including psychological, physical and sexual abuses across the globe. Violence against women, girls, and children is a worrying trend. Data is still scarce on the real picture of the force since most of the members are indoors with abusers and have no opportunity to report. Several police stations around the world have reported a sharp rise in distress calls from homes. Even before the COVID-19 forced lockdowns, the state of domestic violence globally has been high, particularly in low income countries, particularly in Africa and South Asia as shown in Figure 1.

Note: LICs (Low Income Countries)

Source: Authors’ computations based on data from WHO (2019)

Incidence of domestic violence in Africa is particularly concerning, especially in some countries such as Uganda, Cameroon, Democratic Republic of Congo, and Zambia where the proportion of women who had experienced violence in recent period was shocking, exceeding 50%. In most other countries the spread of violence by intimate partners was not that low suggesting that Africa has a record level of women suffering due to violence. It is easy to infer that the COVID-19 would escalate the state of domestic violence in Africa as some of the underlying factors include lack of bargaining power in the household on resource sharing which is aggravated in the COVID-19 world.

Figure 2: Prevalence of domestic violence among women in selected African countries (%)

Source: African Development Report (2015), African Development Bank

Domestic violence against women and children may take the form of psychological, sexual, reproductive, physical or economic violence by an intimate partner or a family member. The broader term is family violence, including elder abuse, child abuse, or just violence between family members. This violence may inflict on the victim’s mental health in the form of anxiety, emotional distress, eating and sleeping disorders, low self-esteem. Available evidence for Africa suggests that there is high degree of correlation between physical, verbal and sexual abuses, sometimes taking place concurrently (see Figure 3). The strength of correlation among the various forms of violence is more pronounced in countries where prevalence of domestic violence is very high, such as Uganda and Zimbabwe, often with limited or no recourse mechanism to hold accountable the perpetrators. Some anecdotal reports indicate that law enforcement, and rule of law tended to have been degraded in the wake of the COVID-19 policy responses.  Hence, reporting domestic violence to law enforcement agencies and getting justice has been impeded by the COVID-19 situation and the likelihood of incidence rising during this time.

Source: African Development Report (2015), African Development Bank

The challenge

With Covid-19, the victims are at home with the abusers. They cannot make distress calls. The health services have diverted to fight the pandemic, and safe houses have converted to isolation centres in some cases. Local organizations may not be having enough money to address the problem. There is little or no access to legal aid and reproductive health services. People are also scared of going to a hospital, for they may contract the disease. The law enforcement is busy enforcing lockdowns and curfews, and if they were to arrest everyone involved, the police cells and jails need to keep the social distance a time when countries are trying to decongest their prisons. The courts in most countries are not operating at full capacity, with most of the judges working online.

Women have always carried a heavy burden in times of crisis. Besides violence, women, girls, and the poorest in the society are likely to bear the responsibility brought about the disease for a long time with a lack of family planning services—early teenage pregnancies. The challenges faced by Covid-19 are unprecedented, and no government or organization had a proper and sufficient plan.

Who is affected by domestic violence?

According to (AMBURG 2016), most victims of domestic abuse are women accounting for 76%. Domestic violence also accounts for 21 percent of violent crimes in the USA. UNFPA estimates 31 million cases of GBV if the lockdown continues for the next six months (UNFPA, 2020) child marriages will also be on the rise sharply given that children are at home for long periods. Lack of reproductive services is likely to affect 47 million women in low from 114 developing countries classified as small, and medium income will not access contraception. Over 7 million unintended pregnancies may arise from a lack of reproductive health services. Rising incandescence of rape and incest due to lockdown will also increase tremendously, and so is teenage pregnancy. Young children are also likely to experience violence either directly or indirectly.

Poverty and intimate partner violence

We are likely to see the rise of economic abuse and social abuse. Low-income women are more likely to experience intimate partner violence, and unemployed men are more likely to perpetrate it. The evidence for Africa suggests that the intensity of violence experienced by women is affected by the type of employment they have. Women that work generally outside of home tend to experience less violence than those that either work for themselves (self-employed) or stay at home to do domestic chorus (Figure 4)

Figure 4: Domestic violence and Women employment (%)

Source: African Development Report (2015), African Development Bank

Women are more likely to work in the service industry that has been affected profoundly. More women are informal wage workers and have lost income. Economic instability prevents women from leaving abusive relationships.

Gender roles

With schools closed and most family members are not working, women mostly bear the burden of care in most societies. In most communities, abuse is justified and accepted as a way of disciplining a woman when she questions the authority of a man. It is more justified in patriarchal societies, and this may go unpunished since it is a norm. Women in most African countries do not own land since men inherit the property from their parents while women do not. Abused women have nowhere to go with their children, and hence they must stay with the abuser.

What can be done?

Improving the rule of law and criminal justice system is as important as treating domestic violence as a public health emergency.

Should we treat domestic violence through the criminal justice system or as a public health emergency? I argue that both are important. There is a need for crisis intervention. As a preventive measure, individuals should be encouraged to be aware of the mental health impacts of COVID-19 and its manifestations due to increased violence, psychological and physical abuse of women, minors and other vulnerable groups. These incidences are likely correlated with measures taken by governments to reduce human contact through reduced mobility. According to data released by Google, lockdowns reduced significantly mobility of people in major cities in Africa. According to Figure 5, information gathered by tracking mobile phone with Google map applications show that movements to retail stores (markets), groceries and  workplaces declined steadily on a daily basis from February 19, 2020 for nearly three months across African cities impacting the livelihoods of millions of people, especially women where  the majority are engaged in retail trade and services. Loss of income, confinement, and caring for family adds to the burden of women and fuels tensions within a household. As a result of these factors, anecdotal evidence and news reports across Africa suggest a rising trend of incidence of domestic violence, sexual abuse of minors, spread of incest and other forms of abuses. Given the significant resource constraints, most African governments are unable to provide income support, nor counselling nor legal protection for the unintended consequences of fighting the pandemic. Still there are practical measures they can take to mitigate the incidence of domestic violence by mobilizing and empowering communities, strengthening civil society organizations as well as educating the law enforcement agencies without incurring significant financial resources.

Figure 5: Patterns of lockdowns in Africa to contain the spread of the virus causing COVID-19

Source: author’s computations based on data provided by Google for 54 African countries (https://www.google.com/covid19/mobility/.)

In cases where families have lost income, alternative income should be considered. Governments and civil society could come up with plans to take care of the vulnerable as they search alternative ways of survival. Citizens should stay informed, avoid too much time on social media, exercise even in self-quarantine, and ensure they have a regular sleep, regular  diet and adjust to the realities of life that has now become a new normal.

Policy and budget Interventions

Domestic violence prevention and control should be included as an essential service. There is a need for all policymakers to include domestic violence as part of the COVID-19 health response plan. Particular emphasis should go to those health workers who are women and maybe experiencing stigma in their homes (World Health Organisation, 2020) . The Kenya civil society (Gitau, 2020) has called for the government to allocate 30% of the money received as donations and loans towards implementing Gender-Based Violence initiatives, including prevention and response strategy.

Judicial systems should prioritize gender-based violence cases, shelters as essential services should be help. A unique code should be developed for those experiencing domestic violence to communicate to the outside world. Sexual reproductive health policy in times of crisis should be done by governments. All COVID-mitigation plans should take into consideration the unique circumstances of the citizens.

Information

Information on gender-based violence should be made available to women and girls in ways that they can access with special considerations to their particular environment. Women should have a safe way of alerting authorities and report abuse. The government should sponsor electronic and social media information so as to address gender-based violence.

Community structures

Empower grass-root organizations and institutions to deal with gender-based violence. Health institutions should also be strengthened, and resources allocated to deal with violence against women and children. In areas where there are online services. Appropriate investment in online services and resources where women can seek help. Information can also be disseminated online. In New York, women can use code words when they visit a pharmacist to alert authorities that they are in trouble.

Bibliography

AMBURG, J. V. (2016, June 2). This is How Many Women and Families are Affected by Domestic Violence. Retrieved from Time: https://time.com/4354035/domestic-violence-statistics/

Gitau, J. (2020, April 28). The Shadow Pandemic: Kenyan Civil Society Demands Concrete Action to Protect Women and Girls During COVID-19. Retrieved from Equality Now: https://www.equalitynow.org/shadow_pandemic

UN chief calls for domestic violence ” ceasefire” amid “horrifying global surge”. (2020, April 6). Retrieved from UN News: https://news.un.org/en/story/2020/04/1061052

UNFPA. (2020, April 27). Impact of the COVID-19 Pandemic on Family Planning and Ending Gender-based Violence, Female Genital Mutilation and Child Marriage [EN/AR]. Retrieved from Relief Web: https://reliefweb.int/sites/reliefweb.int/files/resources/COVID-19_impact_brief_for_UNFPA_24_April_2020_1.pdf

World Health Organisation. (2020, March 26th). COVID-19 and violence against women What the Health Sector/System can do. Retrieved from World Health Organisation hrp Research for Impact: https://www.who.int/reproductivehealth/publications/emergencies/COVID-19-VAW-full-text.pdf

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