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COVID-19 Pandemic and the Health and Well-Being of Vulnerable People in Vietnam

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Handbook of Social Sciences and Global Public Health

Abstract

Despite a sizable population and modest status as a low-middle-income country, Vietnam has recorded a low COVID-19 fatality rate that rivals those of richer countries with far larger spending on health. This chapter offers an early review of the emerging literature in public health and economics on the pandemic effects in Vietnam, with a specific focus on vulnerable population groups. The review suggests that vulnerable workers were at more health risk than the general population. The pandemic reduced household income, increased the poverty rate, and worsened wage equality. It increased the proportion of below-minimum-wage workers by 2.5 percentage points (i.e., a 32-percent increase). While government policy responses were generally regarded as effective, public support for these responses was essential for this success, particularly where there was stronger public participation in the political process. The review also indicates the need for a social protection database to identify the poor and informal workers to further enhance targeting efforts. Finally, it suggests future directions for research in the Vietnamese context.

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Notes

  1. 1.

    Several other studies that analyze the same survey observe a similar finding that the poor were more affected during the pandemic (Bonacini et al. 2021; Papageorge et al. 2021; Aubert et al. 2022).

  2. 2.

    For Fig. 1, the data on COVID deaths are between early 2020 and October 2022 and the public spending data are in 2019, which rules out increased spending in immediate response to the pandemic.

  3. 3.

    Vietnam is well-known among researchers for its high quality micro survey data. The country ranks at position 77 out of 219 countries and territories in the world regarding its statistical performance index (Dang et al. 2023a).

  4. 4.

    The authors do not review medical studies in this chapter. For a recent review paper on this topic, see Dao et al. (2022). Implementing an early systematic review of studies on COVID-19 in Vietnam between May to August 2020 on 72 studies, Dao et al. (2022) find that most of these studies (42%) were about control and prevention of COVID-19, to be followed by studies on virology and genomics, the natural history of the virus and its transmission (18%), and on the investigation into the epidemiology of the COVID-19 pandemic in Vietnam (13%). The authors also find only one study on the development of candidate therapeutics and no study on personal protective equipment or protocol for healthcare workers’ safety.

  5. 5.

    Dang and Trinh (2022) also show that locations without either coal-powered stations or cement stations had even more reduced air pollution in the 2-week period after the lockdown as well as over longer periods. This is because coal-fired power stations were allowed to be in normal operation during the lockdown like most other manufacturing activities (GoV 2020), locations with these power stations might not have been affected by the lockdown and consequently might have not seen reduced air pollution.

  6. 6.

    The Foster-Greer-Thorbecke index is defined as \( {P}_{\alpha }=\frac{1}{n}\sum \limits_{i=1}^q{\left[\frac{z-{Y}_i}{z}\right]}^{\alpha } \) (Foster, Greer and Thorbecke, 1984). Yi is a welfare indicator for person i, z is the expenditure poverty line, n is the total number of people, q is the number of workers below z, and α can be interpreted as a measure of inequality aversion. When α = 0, we have the headcount index H, which measures the proportion of workers below the poverty line. When α = 1 and α = 2, we obtain the poverty gap PG, which measures the depth of poverty, and the squared poverty gap P2, which measures the severity of poverty, respectively. Dang et al. (2023b) estimate Pα with Yi as the monthly wage of workers and z as the minimum wage.

  7. 7.

    There might also be some distributional impacts at the province level. The authors find some evidence that provinces with greater openness to the global economy had higher levels of economic growth and witnessed weaker pandemic effects.

  8. 8.

    Yet, Dang et al. (2021) find some indicative evidence suggests that women in Vietnam tend to have more pessimistic expectations for their future financial situations.

  9. 9.

    The media report that many vulnerable migrant workers in the major cities, who lost their job because of the pandemic, fall into economically precarious situations because of the lockdowns (Chieu 2021; Dinh and An 2021; Reuter 2021; Tran and Dinh 2021).

  10. 10.

    Drawing on lessons learnt during the pandemic from low- and middle-income countries, Tran et al. (2022) introduce a number of case studies to help strengthen the health system and community responses in resource-scarce settings.

  11. 11.

    The findings from academic studies are well supported by stories reported in the local media. Protection measures such as social distancing, washing one’s hands, and staying at home were perceived as actions of patriotism by the public (Le Thu 2020). Perhaps the spirit of the country’s fight against the pandemic is best epitomized in the words of the then Prime Minister Nguyen Xuan Phuc “Every business, every citizen, every residential area must be a fortress to prevent the epidemic” (Pham 2020).

  12. 12.

    As an example for poor staff capacity and discretionary power, Tran-Nam et al. (2021) cite an example where the term “essential goods” was interpreted differently by the police in different localities (i.e., people could leave their home to buy the essential goods during the lockdown). In some extreme cases, bread was not considered food, and hygiene products for women were not considered essential.

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Acknowledgments

The authors would like to thank the editor Pranee Liamputtong, and Jere Behrman, Long Giang, Paul Glewwe, Cuong Le-Van, Khang Ngoc Luu, Cuong Nguyen, and Huong Nguyen for helpful feedback on earlier drafts. They are grateful to the UK Foreign Commonwealth and Development Office (FCDO) for funding assistance through the Data and Evidence for Tackling Extreme Poverty (DEEP) Research Program.

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Correspondence to Hai-Anh H. Dang .

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Appendix A Number of COVID deaths and public spending on health for Vietnam and other countries

Appendix A Number of COVID deaths and public spending on health for Vietnam and other countries

No

Country

Current health exp.

Death per million

Percent of GDP (%)

USD

1

Afghanistan

13

66

205

2

Algeria

6

248

160

3

Andorra

7

2744

2009

4

Angola

3

71

60

5

Antigua and Barbuda

4

760

1503

6

Argentina

10

946

2902

7

Armenia

11

524

2941

8

Australia

10

5427

589

9

Austria

10

5242

2359

10

Azerbaijan

4

193

988

11

Bahamas

6

2005

2139

12

Bahrain

4

940

927

13

Bangladesh

2

46

180

14

Barbados

6

1143

1951

15

Belarus

6

399

753

16

Belgium

11

4960

2861

17

Belize

6

293

1757

18

Benin

2

29

14

19

Bhutan

4

116

28

20

Bolivia (Plurinational State of)

7

246

1931

21

Bosnia and Herzegovina

9

554

4894

22

Botswana

6

482

1208

23

Brazil

10

853

3255

24

Brunei Darussalam

2

672

307

25

Bulgaria

7

698

5396

26

Burkina Faso

5

42

19

27

Burundi

8

21

1

28

Cabo Verde

5

178

746

29

Cambodia

7

113

185

30

Cameroon

4

54

75

31

Canada

11

5048

1213

32

Central African Republic

8

37

24

33

Chad

4

30

12

34

Chile

9

1376

3237

35

China

5

535

19

36

Colombia

8

495

2817

37

Comoros

5

72

188

38

Congo

2

49

72

39

Cook Islands

3

662

57

40

Costa Rica

7

922

1778

41

Croatia

7

1040

4170

42

Cuba

11

1032

753

43

Cyprus

7

1996

1357

44

Czechia

8

1844

3883

45

Côte d’Ivoire

3

75

32

46

Democratic Republic of the Congo

4

21

17

47

Denmark

10

6003

1234

48

Djibouti

2

62

194

49

Dominica

5

440

1031

50

Dominican Republic

6

491

408

51

Ecuador

8

486

2066

52

Egypt

5

150

247

53

El Salvador

7

300

655

54

Equatorial Guinea

3

255

135

55

Eritrea

4

25

29

56

Estonia

7

1599

2048

57

Eswatini

7

264

1239

58

Ethiopia

3

27

68

59

Fiji

4

236

987

60

Finland

9

4450

1128

61

France

11

4492

2265

62

Gabon

3

215

141

63

Gambia

4

30

158

64

Georgia

7

291

4228

65

Germany

12

5440

1822

66

Ghana

3

75

48

67

Greece

8

1501

3106

68

Grenada

5

534

2116

69

Guatemala

6

271

1129

70

Guinea

4

43

36

71

Guinea-Bissau

8

63

92

72

Guyana

5

326

1637

73

Haiti

5

57

76

74

Honduras

7

188

1128

75

Hungary

6

1062

4879

76

Iceland

9

6275

628

77

India

3

64

387

78

Indonesia

3

120

585

79

Iran (Islamic Republic of)

7

470

1743

80

Iraq

4

253

645

81

Ireland

7

5429

1629

82

Israel

7

3456

1375

83

Italy

9

2906

2972

84

Jamaica

6

327

1126

85

Japan

11

4360

360

86

Jordan

8

334

1398

87

Kazakhstan

3

273

1027

88

Kenya

5

83

108

89

Kiribati

10

172

111

90

Kuwait

5

1759

609

91

Kyrgyzstan

4

62

466

92

Lao People’s Democratic Republic

3

68

106

93

Latvia

7

1167

3140

94

Lebanon

9

663

1559

95

Lesotho

11

124

332

96

Liberia

8

53

60

97

Lithuania

7

1370

3348

98

Luxembourg

5

6221

1850

99

Madagascar

4

20

52

100

Malawi

7

30

144

101

Malaysia

4

437

1140

102

Maldives

8

854

580

103

Mali

4

34

38

104

Malta

8

2532

1633

105

Marshall Islands

16

664

289

106

Mauritania

3

58

220

107

Mauritius

6

686

810

108

Mexico

5

540

2589

109

Micronesia (Federated States of)

11

415

483

110

Monaco

2

2906

1617

111

Mongolia

4

163

661

112

Montenegro

8

735

4430

113

Morocco

5

174

446

114

Mozambique

8

39

73

115

Myanmar

5

60

360

116

Namibia

8

427

1636

117

Nauru

10

1049

93

118

Nepal

4

53

420

119

Netherlands

10

5335

1314

120

New Zealand

10

4211

647

121

Nicaragua

8

161

37

122

Niger

6

31

13

123

Nigeria

3

71

16

124

Niue

5

1012

0

125

North Macedonia

7

437

4584

126

Norway

11

8007

779

127

Oman

4

625

930

128

Pakistan

3

39

141

129

Palau

15

2356

333

130

Panama

8

1193

2003

131

Papua New Guinea

2

65

76

132

Paraguay

7

388

2782

133

Peru

5

370

6670

134

Philippines

4

142

586

135

Poland

6

1014

3104

136

Portugal

10

2221

2443

137

Qatar

3

1807

241

138

Republic of Korea

8

2625

562

139

Republic of Moldova

6

284

4426

140

Romania

6

739

3457

141

Russian Federation

6

653

2665

142

Rwanda

6

51

116

143

Saint Kitts and Nevis

5

1088

871

144

Saint Lucia

4

502

2216

145

Saint Vincent and the Grenadines

5

355

1049

146

Samoa

6

272

147

147

San Marino

6

3051

3485

148

Sao Tome and Principe

6

108

358

149

Saudi Arabia

6

1316

274

150

Senegal

4

59

121

151

Serbia

9

641

2458

152

Seychelles

5

840

1729

153

Sierra Leone

9

46

16

154

Singapore

4

2633

282

155

Slovakia

7

1342

3761

156

Slovenia

9

2219

4006

157

Solomon Islands

5

112

228

158

South Africa

9

547

1745

159

South Sudan

6

23

12

160

Spain

9

2711

2439

161

Sri Lanka

4

161

786

162

Sudan

5

47

115

163

Suriname

10

619

2382

164

Sweden

11

5671

1998

165

Switzerland

11

9666

1591

166

Tajikistan

7

62

13

167

Thailand

4

296

472

168

Timor-Leste

7

93

107

169

Togo

6

51

36

170

Tonga

5

242

115

171

Trinidad and Tobago

7

1168

3036

172

Tunisia

7

233

2501

173

Turkmenistan

7

500

0

174

Tuvalu

24

973

0

175

Türkiye

4

396

1213

176

USA

17

10,921

3199

177

Uganda

4

32

82

178

Ukraine

7

248

2482

179

United Arab Emirates

4

1843

240

180

United Kingdom

10

4313

2876

181

United Republic of Tanzania

4

40

15

182

Uruguay

9

1661

2167

183

Uzbekistan

6

99

50

184

Vanuatu

3

104

47

185

Venezuela (Bolivarian Republic of)

5

339

204

186

Viet Nam

5

181

447

187

Zambia

5

69

225

188

Zimbabwe

8

103

383

  1. Note: Data are from WHO (2022a, b). Data on COVID-19 deaths are between early 2020 and October 2022. Data on health expenditures are in 2019

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Dang, HA.H., Do, M.N.N. (2023). COVID-19 Pandemic and the Health and Well-Being of Vulnerable People in Vietnam. In: Liamputtong, P. (eds) Handbook of Social Sciences and Global Public Health. Springer, Cham. https://doi.org/10.1007/978-3-031-25110-8_127

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