Accidental sampling

, 97

Accommodating as conflict

, 242

Accommodation industry

, 324–325

Adashi dashi

, 157

ADF-Fisher Chi-square test

, 253

Advisory Committee on Community Policing (ACCP)

, 50

Advocacy

communication

, 118

public

, 118

Afrexim Bank

, 142

Africa

debt

, 248–250

smart city initiatives in

, 281–282

Africa Gas Pipeline

, 317

African agenda

, 310

African Continental Free Trade Agreement (AfCFTA)

, 29, 34, 41, 352–354

African Continental Free Trade Area (AfCFTA)

, 37–38, 40–41, 61–62, 313

agreement

, 316–317

African Development Bank

, 34

African economies

, 61–62

conceptualising FDI, Trade and COVID-19 scenario for

, 63–67

methodology

, 69–72

neural network analysis for FDI, Trade and COVID-19 scenario

, 72–74

neural network feedforward structure

, 72

review of literature

, 68–69

African geopolitical socioeconomy

, 354

African green deal

economic issues

, 317–318

financing AUGD

, 318

governance issues

, 319

legal/regulatory issues

, 316–317

towards post-COVID-19 recovery

, 316–319

technological issues

, 318–319

African Nationally Determined Contributions Hub (NDCs Hub)

, 310, 316–317, 319

African Renewable Energy Initiative (AREI)

, 313, 318

African Union (AU)

, 6, 310, 318

African Union Green Deal (AUGD)

, 310

Age

, 343

Agrarian

, 156

Agree (A)

, 341

Agricultural commodities

, 82

Agricultural risks

, 164

Agricultural shocks

, 82–83

Agriculture

, 156, 164, 169–170

Agro-processors

, 83–84

AidData dataset

, 185

Alternative Dispute Resolution (ADR)

, 37–38, 41

Analysis of Variance (ANOVA)

, 269–270

Analytical procedure

, 124–125

Angola, socio-economic shocks in

, 35–37

Anthropocentrism

, 311

Anti-Dumping measures (ADP)

, 2, 74

Antithesis of security

, 52

Anxiety

, 52, 102

Artificial intelligence (AI)

, 354

Artisans

knowledge of coronavirus disease

, 98–99

positions on existence of coronavirus disease

, 99

in socio-economic development

, 97–98

Aspirations

, 138

Asset

appropriate documentation of

, 163–164

ownership

, 129

Attitudes

, 138

Augmented Dickey-Fuller model (ADF model)

, 172

ADF unit root test

, 174

Augmented-Solow model

, 189

Automated Teller Machine (ATM)

, 337, 342–343

Automobile Services

, 97

Autoregressive distributed lag (ARDL)

, 170–172, 252

diagnostic test analysis

, 177

results of ARDL estimation

, 174

Auxiliary workers

, 296–297, 299–300

Avoidance

, 242

Balance of trade (BOT)

, 203–204

Behaviour change

, 111–112

Behavioural Immune System

, 296

Big-data

, 354

Bill of Rights

, 37

Bioeconomy Cross-sectoral National Action Agenda

, 355–356

‘Bioregionalism’

, 311

Bivariate extreme regression methods

, 171

Bleeding

, 355

trade

, 355–356

Bound test

, 172

Brazil, Russia, India, China and South Africa (BRICS)

, 250–251

Breast milk, non-infectious COVID-19 viral RNA in

, 110

Breastfeeding

, 109, 111

Budget deficits

, 122–123

Bus rapid transit systems (BRT systems)

, 283–284

Business development

, 1, 156

advance financing systems for

, 159–160

in Rural Nigeria

, 158–159

Capitalism

, 238

Capitalist economies

, 138

Cash-less Nigeria policy

, 338–339

Cashless

economy

, 338

instrument function

, 339

payment system

, 336

Cashless policy

, 338, 346

instruments

, 338, 346

in Nigeria

, 337

Central Bank of Nigeria (CBN)

, 142, 172, 336

Ceteris paribus

, 176–177

China Africa Research Initiative (CARI)

, 4, 185

Chinese debt repayments

, 184–185

Chinese loans

in Africa

, 184–185

composition in African countries

, 185–188

Citizen Social Accountability Engagement Forums

, 17–18

City of Johannesburg (CoJ)

, 282–283, 285

CoJ Smart City Office

, 283

Class demarcations

, 238

Climate change

, 164, 264

Cluster analysis (CA)

, 125

Code of Social Security

, 15–16

Cognitive process

, 97

Collaborating

, 242

Communication

advocacy

, 118

inadequate

, 113–114

structural

, 115

Community-centred tourism

, 327

Companies and Allied Matters Act (2020)

, 33

Companies Income Tax (Amendment) Act Cap

, 33

Company and Allied Matters Act

, 223

Competing

, 242

Compromise management style

, 242

Computational techniques

, 62

Computational techniques

, 69

‘Computer Village’

, 283–284

Conference of the Parties (COP)

, 312

Conflict

, 237

management styles

, 242

Constrained assistance programmes

, 17

Contingency theory

, 222

Cooperative societies

, 158–159

Coping strategies

, 83–84, 299–300

Coronavirus (COVID-19)

, 1, 28, 33–34, 48, 61–62, 96, 202, 219–220, 236–237, 241–242, 250, 264, 296–298, 310, 324, 326, 352

adherence to preventive measures of

, 100–101

in Africa

, 247–248

Africa’s debt

, 248–250

artisans’ knowledge of

, 98–99

artisans’ positions on existence of

, 99

challenges experienced by tomato stakeholders during

, 88–90

challenges faced in workplace environment

, 298–299

challenges in fighting against

, 105

coping strategies

, 299–300

crisis in South Africa

, 296

disease outbreak

, 83

disposition to and adoption of preventive measures against

, 100

empirical literature review

, 252

empirical literature review

, 297–300

and entrepreneurship

, 140–143

factors influencing adherence to existing preventive measures of

, 101–102

household conflict and

, 237–238

loan implications from IMF and World Bank

, 250–251

lockdown strategy

, 325

management strategies, economic well-being and perceived vulnerability

, 103–105

methodology

, 13, 300–301

model specification and estimation of results

, 252–253

and Nigeria experience

, 49–50

Nigeria in

, 83–84

opportunities and challenges of achieving smart cities amid COVID-19 pandemic

, 285–286

opportunities created by

, 145, 148, 150

owners/managers actions to mitigate impacts of COVID-19 on enterprises

, 226–227

pandemic

, 144

pandemic impact on smart cities

, 280

pandemic mitigatory strategies

, 13

performance of Africa’s Health and Educational Sectors in ‘new normal’

, 3

post-COVID economic resilience and development in Africa

, 5–6

rapid urbanisation affecting achievement of smart cities amid

, 286–287

relationship between economic activities of tomato stakeholders before and during

, 85–88

results presentation and analysis

, 253–259

roles of social workers and social auxiliary workers

, 298

sectoral development and trade in post-COVID-19 Africa

, 4–5

services and sustainable development in post-COVID-19 Africa

, 6

shocks during pandemics

, 14–15

small and medium scale enterprises and

, 220–221

social protection in SADC region

, 15–16

socio-economic impact of

, 202–203

socio-economic shocks owing to outbreak of

, 28

socio-psychological effects of perceived vulnerability

, 102–103

socioeconomic shocks and development in Africa

, 1–2

South Africa

, 18–19

sustainable strategies to mitigate challenges

, 20–21

theoretical background

, 251

unintended consequences on achievement of smart cities

, 284–287

working environment

, 297

Zimbabwe

, 16

Correlation matrix

, 191

‘Covid-19 social relief of distress grant’

, 18–19

Credit

constraints

, 129

schemes in Nigeria

, 162

Critical Discourse Analysis (CDA)

, 300

Critical junctures

, 144

Cronbach’s Alpha unwavering quality test

, 341

Cross-tabulation analysis

, 128–129

Crowding-out effect

, 188

Cumulative sum of recursive residuals (CUSUM)

, 174

Cumulative sum of squares of recursive residuals (CUSUMq)

, 174

‘Cybernetically planned cities’

, 280

Data

analysis

, 330–331

collection process

, 327

description

, 123

Debt

, 252–253

Debt Laffer curve theory

, 188, 251

Debt overhang theory

, 188, 251

Democratic party

, 309–310

Department of State Services (DSS)

, 55–56

Descriptive statistics

, 206–208

Desert-to-Power project

, 317

Digital economy, bioeconomy, science, technology and innovation strategy (DEBSTI strategy)

, 355–356

Digital economy and society index (DESI)

, 354

Digital technologies

, 38

Digital trade tools

, 353–354

Digitalisation

, 38–39, 352, 354

in Africa’s agri-food space

, 355

Disagree (D)

, 341

Distributed ledger technologies (DLT)

, 281

Divisional Police Officer (DPO)

, 53

Dynamic panel data model

, 189

‘E-services’

, 281

Ecocentrism

, 311

Economic Community of West African States (ECOWAS)

, 41

Economic crises

, 82–83

Economic development

, 203–204, 325

Economic growth

, 138, 142–143

composition of Chinese loans in African countries

, 185–188

estimation technique

, 189–191

findings

, 195–196

results

, 191–196

theoretical underpinning

, 188–191

transmission channels of external debt to growth of recipient economy

, 188

Economic shocks

, 14, 138

in Africa

, 30

Economic well-being

, 103–105

Economics ramification of pandemic

, 222

Edible backyard

factors affected production during lockdown

, 270

household food security

, 267–269

literature review

, 265–266

methodology

, 269–270

reasons for not considering farming as major occupation

, 271

results

, 270–273

sustainable livelihood

, 266–267

theoretical framework

, 266–269

Eko Atlantic City south of Lagos

, 283–284

Electricity price (ELECTP)

, 203–204

Electronic instalments

, 338

Electronic system

, 336

Electronic-based exchanges

, 338

Embedded opportunities in Nigeria

, 144–149

Emissions Trading Scheme (ETS)

, 315

Emotions

, 54

Employees

, 324

Employment

, 122–123

Employment in Nigeria

, 83–84

Energy sector performance

data sources and measurement of variables

, 203–204

descriptive statistics

, 206–208

estimation technique

, 204–206

impulse response functions and forecast error variance decomposition

, 212–214

Kao residual co-integration result

, 208–212

lag length selection criteria

, 208

methodology

, 203–206

results

, 206–214

socio-economic shocks on

, 203

variance decomposition

, 214

Enterprises

characteristics of

, 223–226

owners/managers actions to mitigate impacts of COVID-19 on

, 226–227

Entrepreneurship

, 138, 156

COVID-19 and

, 140–143

embedded opportunities in Nigeria

, 144–149

insights from literature

, 139–140

policy implications

, 149–150

ERIC database

, 13

Error correction model

, 173–174

Estimation technique

, 189–191

Estimation technique

, 204–206

Esusu practice

, 157

EU Green Deal (EUGD)

, 309–310, 313–314

Euro Area countries (EA countries)

, 252

European Commission’s strategy

, 314

European Investment Bank (EIB)

, 315

European Union (EU)

, 309–310, 314

European Union Green Deal (EUGD)

, 314

EUGD Investment Plan

, 314–315

Exchange rate (ER)

, 172

and employment in Nigeria

, 83–84

Exclusive breastfeeding

, 109

Exogenous growth model

, 188

Exogenous variable

, 205

Expectancy theory

, 238

Explanatory variables

, 124

External Debt-Augmented version of Solow growth model

, 189

External debt-GDP ratio

, 184

F-test

, 172, 177

Face masks

, 148–149

Fear

, 102

of stigmatisation

, 99

Federal Capital Territory (FCT)

, 53–54

Federal Republic of Nigeria (FRN)

, 51–52

Female-headed households (FHHs)

, 122–123

socio-economic and institutional drivers of

, 129–132

socio-economic shocks occasioned by COVID-19 pandemic for

, 125–127

vulnerability indices of

, 128–129

Finance in rural Nigeria and small business development

, 157–158

Financial crises

, 324

Financial dualism

, 157

Financial effect of COVID-19

, 324

Financial transaction

, 341–342

Financial transactions

, 336–337, 343

Financing AUGD

, 318

Fintech innovation

, 354

First-time mothers

, 117

Fiscal policy

, 248

Fisher-type tests

, 253

Fixed effects model (FE model)

, 140, 252–253, 256

Food

, 264

food and beverage industry

, 324–325

insecurity

, 264

research community

, 264

security

, 1, 265

Food, Health and Trade Systems

, 352–354

Forecast error variance decomposition

, 212–214

Foreign direct investment (FDI)

, 2, 318

and COVID-19 Scenario for African economies

, 63–67

Foreign Direct Investment Inflows (FDII)

, 74

Foreign Direct Investment Outflows (FDIO)

, 2, 74

Foreign Direct Investment Stock (FDIS)

, 74

Formal finance

, 158

Formal financial system

, 156

Formal financing. See also Informal financing

, 159

Fourth Industrial Revolution (4IR)

, 282, 284

case Lagos, Nigeria

, 283–284

case of Accra, Ghana

, 283

case of Johannesburg, South Africa

, 282–283

Free Trade Zones (FTZs)

, 353

Fundamental human rights of citizens

, 29

Gauteng City-Region Observatory (GCRO)

, 283

Gender

, 343

analytical procedure

, 124–125

and COVID-19 response strategy

, 132–133

data description and sampling technique

, 123

explanatory variables

, 124

inequality

, 13

methodology

, 123–125

results

, 125–132

socio-economic and institutional drivers of MHHs and FHHs vulnerability

, 129–132

socio-economic shocks occasioned by COVID-19 pandemic for MHHs and FHHs

, 125–127

vulnerability indicators

, 124

vulnerability indices of FHHs and MHHs

, 128–129

General Household Survey (GHS)

, 123

Ghana, socio-economic shocks in

, 35–37

Global Chinese Official Finance Database of Aid-Data

, 185

Global economic indicators

, 122–123

Global economic shutdown

, 67

Global financial crises

, 324

Global food crisis

, 265–266

Global health pandemic

, 248–249

Global poverty

, 122–123

Globalisation for African economies

, 67

GMM panel VAR estimation

, 191–192, 194

Google Scholar

, 13

Governance issues

, 319

Government debt (GOVTD)

, 203–204

Government expenditures

, 122–123

Granger causality tests

, 191

Grecian tourism

, 327

Greece economy

, 330–331

Green deal arrangements

, 313–315

green deal funding plan and COVID-19 rethink

, 314–315

US Green New Deal and EU Green Deal

, 313–314

Green deal funding plan

, 314–315

‘Green new deal’ concept

, 309–310

Green recovery

building blocks for African green deal towards post-COVID-19 recovery

, 316–319

green deal arrangements

, 313–315

green theory framework

, 311–313

literature review, theoretical framework and methodological approach

, 311–313

methodological approach

, 313

perceptions of and responses to unprecedented climatic and health events

, 311

Green theory

, 311, 313

of value

, 311

Greenhouse gases (GHGs)

, 314

Gross Domestic Product (GDP)

, 2, 61–62, 169–170, 220

of African economies

, 74

growth

, 83–84, 122–123

Gross Domestic Product per capita (GDPPC)

, 203–204

Growth model

, 188

Growth nexus

, 252

Health crisis

, 219–220

High transaction costs

, 163

High-income countries (HICs)

, 14

Highly Indebted Poor Countries (HIPC)

, 249–250

Home gardening

, 265

Hospitalisations

, 354

Hospitality sector

, 327

Household conflict

, 241–242

and COVID-19

, 237–238

household challenges and conflict during COVID-19 lockdown in Nigeria

, 238–240

management

, 237

management styles

, 242

methodology

, 241

theoretical review

, 238

Violence against Persons (Prohibition) Act

, 240–241

Household food security

, 267–269

Housing Construction services

, 97

Human capital

, 30

Human Rights Violation (HRV)

, 52–53

Human Rights-Based framework for social protection

, 13

Humanitarian crisis management

, 1

Hypotheses testing

, 330–331

summary of test of hypotheses

, 331

ICT for Accelerated Development (IC4AD)

, 283

Ida (Tropical cyclone)

, 309–310

Im Pesaran Shin (IPS)

, 208

Impulse response functions (IRF)

, 212–214

In-depth interview (IDI)

, 97, 221

In-kind transfers

, 19

Inadequate communication

, 113–114

Inadequate information

, 117

Income

, 343

shocks

, 83

Inferential statistics

, 85

Inflation (INF)

, 83–84, 172, 203–204, 256–257

Informal finance institutions

, 158

Informal financing

options

, 158–159

systems

, 157

Informal groups

, 158–161

Information and Communication Technology (ICT)

, 336

Innovation

, 138

Insecurity

, 51–52

corona virus and Nigeria experience

, 49–50

literature review

, 49–50

materials and methods

, 49

policy recommendations

, 56

security and insecurity

, 51–52

security situation in Nigeria

, 47–48

selected incident of security bridge during COVID-19 pandemic in Nigeria

, 52–54

socio-economic impact of COVID-19 pandemic lockdown policy in Nigeria

, 54–56

theoretical framework

, 50–51

Inspector General of Police (IGP)

, 48–49

Institutional drivers of MHHs and FHHs vulnerability to COVID-19–related shocks

, 129–132

Institutional financing options

, 158–159

Institutional theory

, 50, 341–342

Insufficient ownership records

, 163–164

Intended NDCs (INDCs)

, 316–317

Intending

, 110

International Air Transport Association (IATA)

, 325

International Covenant on Civil and Political Rights

, 39

International Monetary Fund (IMF)

, 5, 34, 69, 142, 184, 248, 250

loan implications from

, 250–251

Islamic Development Bank

, 142

Jarque-Bera statistic

, 206, 208

Job losses

, 222–223

Johansen co-integration approach

, 171, 252

Jordan economy

, 327

Jordan tourism sector

, 327

K-means approach

, 125

Kano State, Nigeria

, 84

Kao residual co-integration result

, 208, 210, 212

Kenya, socio-economic shocks in

, 35–37

Kenyan Constitution

, 37

Key Informant Interview (KII)

, 97

Knowledgeable audience

, 110

Kurtosis

, 206, 208

Lag length selection criteria

, 208–209

Lag order selection

, 193

Lagos, Nigeria

cash-less Nigeria policy

, 338–339

definition of variables

, 342–343

history of payment systems

, 337–338

methodology

, 340–343

model specification

, 341–342

research design and sample

, 340

research instrument and reliability

, 340–341

results

, 343–346

results from descriptive analysis

, 343–344

results from regression analysis

, 344, 346

review of literature

, 337–339

Legal strategies for addressing socio-economic shocks in Africa

, 37–39

Legal system

, 28

effects in addressing socio-economic shocks in Africa

, 32–34

hurdles against legal systems in addressing socio-economic shocks in Africa

, 34

Levin Lin Chu (LLC)

, 208

Library-based doctrinal legal research technique

, 29

Likert scale

, 341

Liquidity constraint theory

, 188

Livelihood diversification

, 131–132

Living Standards Measurement Study–Integrated Surveys on Agriculture (LSMS-ISA)

, 123, 160

Loan implications from IMF and World Bank

, 250–251

Local Government Areas

, 273

Lockdown

, 222–223, 237–238, 264

conflict during

, 237

defaulting against

, 102

household challenges and conflict during COVID-19 lockdown in Nigeria

, 238–240

measures

, 17

process of implementing lockdown measures

, 105

travelling restriction during

, 100

Logit regression method

, 342

Long-run estimates analysis

, 174–175

Low economic activity

, 163

Low-middle income countries (LMCIs)

, 14

Macroeconomic variables

, 83–84

MainOne’s Lagos Digital Plan

, 283–284

Male-headed households (MHHs)

, 122–123

socio-economic and institutional drivers of

, 129–132

socio-economic shocks occasioned by COVID-19 pandemic for

, 125–127

vulnerability indices of

, 128–129

Market failures

, 138

Masked heroes

, 301

Mass media

, 96

MEDLINE database

, 13

Mental health hazards

, 296

Merchandise Exports (MEXP)

, 74

Merchandise Imports (MIMP)

, 74

Merchandise trade

, 191

Metropolitan municipalities

, 282–283

Micro, small and medium enterprises (MSMEs)

, 156, 159

Migrant workers

, 20

Miscommunication

, 115–116

Mobile banking (MOBK)

, 337, 342–343

Mobile payment system

, 337

Modus operandi

, 29

Motive behind entrepreneurship

, 139

Multi-stage sampling technique

, 84

Multiannual financial framework (MFF)

, 310, 315

Multilateral Debt Relief Initiative (MDRI)

, 249–250

Multiple case study design

, 280

Multiple component analysis (MCA)

, 125

National Association of Small and Medium Scale Industries (NASSI)

, 221

National economic indicators

, 122–123

National Human Rights Commission (NHRC)

, 48–49

National Social Protection Policy Framework

, 16–17

for Zimbabwe

, 17

Necessity entrepreneurship

, 138–139

Network information

, 72–74

Neural network

, 69

analysis for FDI, Trade and COVID-19 scenario

, 72–74

feedforward structure

, 72

New Partnership for Africa’s Development (NEPAD)

, 316

Next Generation EU (NGEU)

, 310

Nigeria

, 82, 169–170

corona virus and Nigeria experience

, 49–50

COVID-19 in

, 83–84

embedded opportunities in

, 144–149

household challenges and conflict during COVID-19 lockdown in

, 238–240

issues and prospects for sustainable finance and credit schemes in rural systems in

, 162

security situation in

, 47–48

selected incident of security bridge during COVID-19 pandemic in

, 52–54

socio-economic impact of COVID-19 pandemic lockdown policy in

, 54–56

socio-economic impact of lockdown in

, 49

socio-economic shocks in

, 35–37

Nigeria COVID-19 National Longitudinal Phone Survey

, 123

Nigeria Customs Service (NCS)

, 55–56

Nigeria Police Force (NPF)

, 48–49

Nigeria Security and Civil Defence Corps (NSCDC)

, 47–48

Nigeria’s Centre for Disease Control (NCDC)

, 48–49, 83

Nigeria’s Companies Allied Matters Act

, 41–42

Nigerian Agricultural Credit Banks (NACB)

, 225

Nigerian Bureau of Statistics (NBS)

, 123, 221

Nigerian Constitution

, 37

Nigerian economy

, 236

Nigerian Immigration Service (NIS)

, 55–56

Nigerian Police Force (NPF)

, 49

Nigerian Stock Exchange

, 35–36

Nigerian tourism industry

, 324

business effect of COVID-19 pandemic in

, 326

conceptual clarifications and linkages

, 324–325

COVID-19 and

, 330

data analysis and hypotheses testing

, 330–331

empirical studies/perceived gaps

, 326–327

empirics

, 328–331

insight from literature

, 324–327

methodological approaches

, 327

respondents profile

, 328

responses to research questions

, 328–330

tourism sector affected most by

, 331

Non-agricultural shocks

, 83

Non-infectious COVID-19 viral RNA in breast milk

, 110

Nudge theory

, 355

‘Off-the-books’ entrepreneurs

, 139

Oil palm. See Palm oil (Elaeis guineensis)

Oil price shock

, 33–34

Oil production (OILP)

, 203–204

Oil shocks

, 82–83

Online platforms

, 298–299

Operational credit

, 273

Opportunity entrepreneurship

, 139

Opportunity-driven entrepreneurships

, 138–139

Ordered logistic model

, 125

Ordinary Least Squares (OLS)

, 69, 252

estimator

, 172

Organisation for Economic Co-operation and Development (OECD)

, 34, 61–62, 138

Orthogonalised Impulse Response Functions (OIRFs)

, 197

Osun State, Nigeria, coronavirus disease in

adherence to preventive measures of COVID-19

, 100–101

artisans in socio-economic development

, 97–98

artisans’ knowledge of coronavirus disease

, 98–99

artisans’ positions on existence of coronavirus disease

, 99

challenges in fighting against COVID-19

, 105

COVID-19 management strategies, economic well-being and perceived vulnerability

, 103–105

disposition to and adoption of preventive measures against coronavirus disease

, 100

factors influencing adherence to existing preventive measures of COVID-19

, 101–102

findings

, 105–106

methodology

, 97

PMT

, 97

research and socio-economic issue

, 96

socio-psychological effects of perceived vulnerability to COVID-19

, 102–103

Osusu

, 157

Out-of-court settlements

, 36

Paired samples t-test

, 85

Palm oil (Elaeis guineensis)

, 169–170

analysis of ARDL diagnostic tests

, 177

analytical procedure

, 172

insights from literature

, 171–172

long-run estimates analysis

, 174–175

method of analysis

, 172–174

model specification

, 173–174

results of ARDL estimation

, 174

short-run estimates analysis

, 176–177

sources of data

, 172

unit root test estimation

, 174

Pandemic preparedness

, 352–354

Pandemics

, 138, 149, 156

measures during

, 14–15

shocks during

, 14–15

Panel data model

, 252

Panel quantile process

, 257–259

Panel unit root test

, 193

Panel VAR model

, 190

Payment system

, 336–338

Pearson correlation analysis

, 327

Pearson’s chi-squared test of independence

, 128–129

Perceived vulnerability

, 103–105

Personal digital assistant (PDA)

, 342–343

Personal protective equipment (PPE)

, 144, 301

Physical health hazards

, 296

Point of Sale machine (POS machine)

, 342–343

Point of Sale Terminal transaction (POS transaction)

, 337

Population density

, 162

Post-COVID-19 era

, 313

Poverty

, 142–143

PP-Fisher Chi-square test

, 253

Practicing

, 110

Pre-knowledgeable audience

, 110

Presupposition

, 301

Preventive measures

, 96

disposition to and adoption of preventive measures against coronavirus disease

, 100

Price fluctuations of palm oil

, 170

in Nigeria

, 170–171

Protection motivation theory (PMT)

, 97

Public advocacy

, 118

Public Health Emergency of International Concern

, 96

Public services

, 282–283

Public-private partnerships (PPPs)

, 283

PubMed

, 13

Qualitative approach

, 280

Qualitative thematic analysis

, 280

Quantile regression models

, 252

Questionnaires

, 340–341

Rapid urbanisation affecting achievement of smart cities

, 286–287

Recovery and Resilience Facility (RRF)

, 315

Recovery from socio-economic shocks in Africa

, 28

Regional Economic Communities (RECs)

, 310

Regional economic cooperation and integration

, 40

Regression models

, 69

Regulatory reforms

, 36

Reliability test

, 341

Reluctant entrepreneurs

, 139

Research

design and sample

, 340

instrument

, 340–341

questionnaire

, 343

reliability

, 340–341

Resilience among breastfeeding mothers

behavioural issues

, 116–117

findings

, 111–116

inadequate communication

, 113–114

inadequate information

, 117

methodology

, 111

miscommunication

, 115–116

non-infectious COVID-19 viral RNA in breast milk

, 110

research approach

, 111

structural communication

, 115

structural issues

, 117–118

theoretical framework

, 110

unplanned pregnancies and need for behaviour change

, 111–112

Respondents profile

, 328–330

Response strategies for post-COVID

, 121–122

Return on assets (ROA)

, 339

Return on equity (ROE)

, 339

Rural areas

of developing countries

, 156–157

entrepreneurship and business development in

, 156

of higher population density

, 162

Rural dwellers

, 156

Rural Nigeria

finance in

, 157–158

institutional financing options for socioeconomic shocks and business development in

, 158–159

SADC region, social protection in

, 15–16

Sage Journals Online

, 13

Sampling technique

, 123

SARS-CoV-2

, 96

Sasakawa Africa Association (SAA)

, 83–84

Schwarz’s Information Criterion (SIC)

, 172

Secondary School Certificate (SSCE)

, 328

Security

, 51–52

sector

, 55–56

Self-actualisation entrepreneurs

, 139

Self-efficacy

, 97

Semi-formal finance

, 158

Services exports (SEMP)

, 2, 74

Services imports (SIMP)

, 2, 74

Shock(s)

, 82–83, 138

mitigation

, 121–122

during pandemics

, 14–15

Short-run estimates analysis

, 176–177

Sine qua non

, 36

Skewness

, 206, 208

Skype

, 33

Small and medium enterprises (SMEs)

, 219–220, 319

Small and medium scale agro-allied manufacturing enterprises (SSAMEs)

, 220

characteristics of enterprises

, 223–226

government

, 229

literature and theoretical framework

, 221–223

methodology

, 221

owners/managers

, 229

owners/managers actions to mitigate impacts of COVID-19 on enterprises

, 226–227

small and medium scale enterprises and COVID-19 pandemic

, 220–221

Small business development, finance in

, 157–158

Smart City

, 280–281

COVID-19 pandemic impact on

, 280

Fourth Industrial Revolution

, 282–284

initiatives in Africa

, 281–282

methodology

, 280

opportunities and challenges of achieving smart cities

, 285–286

rapid urbanisation affecting achievement of smart cities

, 286–287

unintended consequences of COVID-19 pandemic on achievement of

, 284–287

Smart City Growth and Development Strategy 2040

, 282–283

Social auxiliary workers, roles of

, 298

Social Behaviour Change Communication (SBCC) model

, 110

Social distancing

, 28–29, 35–36

Social insurance

, 12, 16–17, 239

Social legislation

, 12

Social network financing

, 159

Social protection

, 11–12

fundamentals in

, 12

Human Rights-Based framework for

, 13

interventions

, 14

in SADC region

, 15–16

transformation document

, 16–17

Social safety nets

, 36–37

Social Service Professions Amendment Act

, 297–298

Social services

, 297

workers

, 298, 300

Social shocks

, 14

Social support networks

, 158

Social transfers

, 12

Social workers

, 296–297, 299–300

roles of

, 298

SocINDEX

, 13

Socio-economic challenges

, 11–12

Socio-economic development, artisans in

, 97–98

Socio-economic impact

, 54–55

of COVID-19 pandemic lockdown policy in Nigeria

, 54–56

security sector

, 55–56

Socio-economic of MHHs and FHHs vulnerability to COVID-19–related shocks

, 129–132

Socio-economic shocks

, 122–123

in Africa

, 28

comparison of legal and regulatory responses in Nigeria, Ghana, Angola, Kenya, South Africa in addressing

, 35–37

data sources and measurement of variables

, 203–204

descriptive statistics

, 206–208

on energy sector performance

, 203

estimation technique

, 204–206

hurdles against legal systems in addressing

, 34

impulse response functions and forecast error variance decomposition

, 212–214

Kao residual co-integration result

, 208–212

lag length selection criteria

, 208

legal strategies for addressing

, 37–39

legal system effects in addressing

, 32–34

literature review

, 31–39

methodology

, 29

methodology

, 203–206

occasioned by COVID-19 pandemic for MHHs and FHHs

, 125–127

results

, 206–214

results and findings

, 40–41

in Rural Nigeria

, 158–159

statement of problems

, 30–31

variance decomposition

, 214

Socio-psychological effects of perceived vulnerability to COVID-19

, 102–103

Socioeconomic randomness

, 354

Socioeconomic sustainability tools

, 354

South Africa

, 248

cash-based transfers

, 18–19

challenges

, 19–20

challenges faced in workplace environment

, 298–299

coping strategies

, 299–300

COVID-19 crisis in

, 304

COVID-19 in

, 18–19

empirical literature review

, 297–300

in-kind transfers

, 19

methodology

, 300–301

roles of social workers and social auxiliary workers

, 298

socio-economic shocks in

, 35–37

wages labour markets

, 19

South African Council for Social Service Professions (SACSSP)

, 297–298

Special Anti-Robbery Squad unit (SARS unit)

, 49, 54

Special Economic Zones (SEZs)

, 353

Stability test

, 196, 211

Stakeholders

, 83–84

challenges experienced by

, 88–90

characteristics

, 85–86

re-alignment and commitment

, 40–41

relationship between economic activities of tomato

, 85–88

Standard deviation (SD)

, 206–208

STATA software

, 269–270

Stigmatisation, fear of

, 99

Stringency Index

, 63

Strongly Agree (SA)

, 341

Strongly Disagree (SD)

, 341

Structural adjustment programmes

, 184

Structural communication

, 115

Structural Panel Vector Autoregressive model (SPVAR model)

, 204–205, 210–211

Sub-Saharan Africa (SSA)

, 68, 141–142, 156

Survey research technique

, 340

Sustainable Development Goals (SDGs)

, 15, 264, 266, 314

SDGs 1

, 13, 266

SDGs 1. 3

, 11–12

SDGs 10

, 13

SDGs 12

, 266

SDGs 2

, 266

SDGs 4

, 266

Sustainable energy

, 203

Sustainable Europe Investment Plan (SEIP)

, 314–315

Sustainable finance in Nigeria

, 162

Sustainable food production

, 264

Sustainable Livelihoods (SLs)

, 266–267

Sustainable strategies to mitigate challenges

, 20–21

Systemic Functional Linguistic theory

, 300

t-test

, 85, 87

Tariff measures (TRFF)

, 2, 74

Tax revenues

, 14–15

Technological issues in African green deal

, 318–319

Teleworking

, 298–299

Textual function, n

, 300

Theory of conflict

, 238

Tomato

, 82

challenges experienced by tomato stakeholders during COVID-19 pandemic

, 88–90

characteristics of tomato stakeholders

, 85–86

literature review

, 83–84

methodology

, 84–85

relationship between economic activities of tomato stakeholders

, 85–88

results

, 85–90

value chain

, 82

Total cost of production (TCP)

, 172

Total factor productivity (TFP)

, 253

Tourism sector

, 324

Trade

and COVID-19 scenario for African economies

, 63–67

facilitation technologies

, 353

tech

, 354

‘Traditional Urbanism’ approach

, 285

‘Tragedy of commons’

, 311

Transformation document social protection

, 16–17

Transmission channels of external debt

, 188

Transportation

industry

, 324–325

restrictions

, 90

Travel industry

, 324–325

U-shaped hypothesis

, 142–143

UN sustainable development goal 7 (SDG 7)

, 319

Undecided (U)

, 341

Unemployment

, 203–204

Unemployment Insurance Fund

, 36

Unified Management Model

, 282–283

Unintended consequences of COVID-19 pandemic on smart cities achievement

, 284–287

Unit root test

estimation

, 174

results

, 254–255

United Nations Conference on Environment and Development

, 266–267

United Nations Conferences on Trade and Development (UNCTAD)

, 69

United Nations Declaration on Human Rights

, 12–13

United Nations Educational Scientific and Cultural Organization

, 29

United Nations Food Systems Summit

, 355

United States (US)

, 309–310

United States Department of Agriculture (USDA)

, 172

University of Uyo Teaching Hospital (UUTH)

, 53

Unplanned pregnancies

, 111–112

Unrestricted Error Correction Model (UECM)

, 173

Urban agriculture (UA)

, 272

Urban development plan

, 280

Urbanisation

, 280

US Green New Deal (USGND)

, 309–310, 313–314

‘Utopian’ style of city

, 283–284

Validity test

, 341

Variance decomposition

, 214

Veronica bucket

, 148–149

Violence against Persons (Prohibition) Act

, 240–241

Virtual technologies

, 39

Vulnerability

, 12

of FHHs and MHHs

, 128–129

index

, 125

indicators

, 124

Vulnerable groups

, 122

Wages labour markets

, 19

Welfare

, 174–175

influence of price mechanism and fluctuations on

, 171

of palm oil producers

, 170–171

of rural households

, 171

Well-being of social service workers

, 297–298

West African Power Pool

, 317

World Bank

, 15, 34, 142

loan implications from

, 250–251

World Development Indicator and Trading Economics

, 203–204

World Development Indicators (WDI)

, 191

World Economic Outlook

, 61–62

World Health Organisation (WHO)

, 29, 96, 110, 144

World Trade Organization (WTO)

, 69, 220

Zimbabwe, COVID-19 in

, 16

challenges

, 16–18

Zoom app

, 33