10.24265/horizmed.2024.v24n3.04

Original Article

 

Influenza-like illnesses in the Peruvian health system

 

Walter Enrique   Prudencio León *1,2 0000-0002-2514-5818

María Verónica   Changano Rodríguez 1 0000-0003-3508-3179

 

1.Hospital Central FAP (Central Hospital of the Peruvian Air Force). Lima, Peru.

2.Universidad Peruana Unión, School of Human Medicine. Lima, Peru.

 

a. Epidemiologist

b. professor of Epidemiology

c. master’s degree in Public Health

 

ABSTRACT

Objective: To determine the behavior and healthcare trends of influenza-like illnesses (ILIs) in the Peruvian health system from 2018 to 2022.

Materials and methods: An observational, descriptive, retrospective study which analyzed the behavior of healthcare visits for ILIs in Peru, using the open database of Superintendencia Nacional de Salud (SUSALUD - National Superintendency of Health). The variables included diagnoses compatible with ILIs according to the International Classification of Diseases, 10th Revision (ICD-10), age groups, sex, location and period of care. The statistical analysis was performed using Microsoft Excel 365 and Stata 18.

Results: Between 2018 and 2022, ILIs generated an average of 2,576,325 outpatient visits per year (range: 1,790,821- 3,710,299), which accounted for 4.9 % of all outpatient visits in the Peruvian health system. Fifty percent of outpatient visits for ILIs occurred at the Ministry of Health (MINSA) services; in contrast, 51 % of emergency department visits for ILIs occurred at the Seguro Social de Salud (EsSalud - Social Security Health Insurance) services. Emergency services recorded 1,077,584 visits annually (range: 312,306-1,644,758), coded according to ICD-10, which accounted for 15 % of all causes treated in these services. Meanwhile, hospitalization services reported 56,587 hospitalizations per year (range: 46,338-67,233), representing 2.9 % of all hospitalizations in the Peruvian health system, where 60.6 % of ILI-related hospitalizations were in MINSA’s services.

Conclusions: In the Peruvian health system, ILIs pose a recurrent healthcare problem each year, with the health services of MINSA and EsSalud being the most in demand.

 

Keywords: Influenza, Human; Respiratory Tract Infections; Health Systems; Global Burden of Disease. (Source: MeSH NLM)

 

INTRODUCTION

ILIs pose a significant socioeconomic and morbidity- mortality burden worldwide. It is estimated that between three and five million cases will occur, with many patients experiencing a severe episode (1). In addition, ILIs are of particular concern among vulnerable populations, as they can lead to epidemic outbreaks and are a common cause of hospitalization and death (2).

Estimates regarding outpatient visits, emergency department visits and hospitalizations for ILIs are very limited in low- and middle-income countries such as Peru. Accurate influenza and ILI disease burden estimates are crucial for informed public health decision-making, as they help national and local decision-makers in monitoring epidemiological trends, planning, allocating resources and promoting influenza vaccination (3).

Influenza and ILIs activities decreased due to public health and social measures implemented in response to COVID-19 (4). However, a rebound in influenza virus activity is anticipated, given the relaxation of these public health and social measures and the low population immunity against influenza (5). Therefore, monitoring influenza and ILIs activity remains critical in the post-COVID-19 era (6).

The Peruvian health system is characterized by fragmentation across financing, insurance and healthcare delivery. The State plays a guiding role through the Ministry of Health (MINSA) (7).

This study aims to describe the epidemiology of ILIs within the Peruvian health system from 2018 to 2022. The findings will provide valuable insights into the impact of ILIs on the Peruvian health system and offer clues for decision-making regarding their prevention and mitigation.

MATERIALS AND METHODS

 

Study design and population

An observational and retrospective study was conducted using secondary data, with the aim of characterizing the behavior of ILIs in Peru from January 1, 2018 to December 31, 2022. The database employed in the study was collected from monthly reports submitted by Instituciones Prestadoras de Servicios de Salud (IPRESS - Peruvian Health Service Provider Institutions) to Superintendencia Nacional de Salud (SUSALUD - National Superintendency of Health). The information was accessible via the SUSALUD website (8), which includes data reported by institutions affiliated with Sistema Nacional Coordinado y Descentralizado de Salud (SNCDS - National Coordinated and Decentralized Health System), such as the health services from MINSA, Dirección Regional de Salud (DIRESA - Regional Health Directorate), Seguro Social de Salud (EsSalud - Social Security Health Insurance), the Armed Forces and Police Forces medical services, private centers and others.

SUSALUD’s open databases include information on diagnoses, coded according to the International Classification of Diseases, 10th Revision (ICD-10) (9). These databases also provide data on the total number of patients seen per month, the type of IPRESS, the location of the healthcare provider (by department, province and district), the period of care (by year and month), and the age and sex of patients treated in outpatient, emergency and hospitalization services.

The study included all registered cases with ICD-10 diagnoses compatible with ILIs, according to MINSA’s standards (10).

Variables and measurements

ILIs are defined based on ICD-10 diagnoses of any event documented in hospitalization, emergency and outpatient records, in accordance with the criteria established in Health Directive No. 061-MINSA (10). The conditions were categorized into two groups: upper respiratory infections and pneumonias. These conditions were analyzed according to the following variables: sex (male or female), age (according to SUSALUD classification), the health subsystem in which the cases were treated (MINSA, EsSalud, Armed Forces medical services, private centers and others) and the year of care (2018, 2022). The location (department) where care was administered was used to estimate the cumulative incidence rates.

Statistical analysis

The statistical analysis was performed using Stata 18 for Windows (StataCorp, College Station, TX, USA) and Excel 365 (Microsoft, WA, USA).

A descriptive analysis was conducted, with the variables represented in frequency tables showing both absolute and relative percentages. For the inferential analysis, a chi-square test was performed, with a significance level set at p < 0.05.

Ethical considerations

Since secondary data (open data) were used and were publicly available on the SUSALUD website, the study was not submitted for review by an ethics committee.

RESULTS

Outpatient visits

ILIs in the Peruvian health system generated an average of 2,576,325 outpatient visits per year (range: 1,790,821-3,710,299), which accounted for 4.98 % (range: 2.11 %-7.03 %) of all outpatient visits in SUSALUD over the five-year evaluation period. The years with the lowest number of visits were the COVID-19 pandemic years, i.e., 2020 and 2021, representing 2.11 % and 4.48 % of the total outpatient visits, respectively. Differences were found in rates across departments and years of care (p = 0.01), with the lowest rate recorded in Lambayeque (380 cases per 100,000 inhabitants) and the highest in Cajamarca (48,382 cases per 100,000 inhabitants) (Table 1). The female sex accounted for 55.3 %. Children under five years of age accounted for 30 % of ILI cases, while individuals over 65 years of age accounted for 8.25 % (Table 4). Pneumonia was diagnosed in 1.3 % of ILI cases, and 50.45 % were treated in MINSA’s services. The estimated annual rates of ILIs by region showed significant differences between the coast, highlands and jungle (p = 0.01), with the lowest rate of outpatient visits for ILIs on the coast (2,949 cases per 100,000 inhabitants) in 2020, and the highest rate in the highlands (14,112 cases per 100,000 inhabitants) in 2019 (Table 5).

 

Table 1.Number of visits and rates of ILIs in outpatient services across departments and years of care

 

 

 

 

 

 

Outpatient visits

 

 

 

 

 

Period

2018

 

2019

 

2020

 

2021

 

2022

 

 

n

Rate

n

Rate

n

Rate

n

Rate

n

Rate

Peru

3,603,533

11,417

3,710,299

11,547

1,790,821

5,489

1,481,894

4,486

2,295,081

6,872

Amazonas

25,182

5,998

19,638

4,633

3,027

709

3,642

850

9,026

2,102

Ancash

222,348

19,243

230,581

19,716

60,544

5,128

69,493

5,848

108,496

9,086

Apurímac

43,857

10,263

33,294

7,750

9,390

2,180

6,868

1,595

16,535

3,848

Arequipa

414,454

29,009

455,724

31,115

180,014

12,021

214,461

14,048

347,932

22,390

Ayacucho

83,907

12,731

110,971

16,700

56,738

8,491

63,138

9,424

110,247

16,441

Cajamarca

257,043

17,871

287,622

19,865

703,339

48,382

93,596

6,432

181,014

12,448

Callao

190,124

17,624

192,502

17,413

25,621

2,268

10,004

869

16,796

1,434

Cusco

135,378

10,252

144,756

10,799

58,162

4,286

109,531

7,995

154,939

11,223

Huancavelica

50,441

13,403

76,367

20,570

15,423

4,222

21,087

5,884

30,154

8,595

Huánuco

136,455

18,015

121,659

16,011

53,452

7,031

39,640

5,227

45,291

5,997

Ica

129,512

14,029

188,683

19,859

44,082

4,520

80,242

8,039

97,661

9,574

Junín

181,811

13,617

241,027

17,854

122,228

8,978

256,018

18,701

233,466

16,989

La Libertad

164,095

8,465

168,023

8,486

65,643

3,255

81,720

3,989

142,998

6,884

Lambayeque

16,548

1,303

20,439

1,582

4,975

380

6,469

488

13,427

1,003

Lima

1,125,927

11,059

982,614

9,434

212,703

2,001

258,268

2,388

455,361

4,145

Loreto

40,727

4,071

38,627

3,805

10,027

976

16,478

1,589

21,932

2,099

Madre de Dios

7,335

4,547

8,255

4,923

2,378

1,368

1,077

599

744

401

Moquegua

47,381

25,423

40,574

21,379

4,264

2,212

3,842

1,968

9,722

4,927

Pasco

35,105

12,920

37,620

13,823

8,134

2,991

9,492

3,505

15,116

5,613

Piura

67,520

3,420

88,266

4,384

21,083

1,029

32,729

1,576

59,980

2,852

Puno

92,551

7,483

58,000

4,681

23,634

1,909

16,801

1,362

35,999

2,935

San Martín

35,682

4,116

44,801

5,066

50,402

5,602

63,870

6,998

126,049

13,636

Tacna

22,933

6,466

29,366

8,085

11,502

3,100

9,822

2,599

17,246

4,489

Tumbes

29,844

12,367

46,395

18,806

6,655

2,646

3,436

1,344

6,999

2,697

Ucayali

47,373

8,478

44,495

7,745

37,401

6,349

10,170

1,688

37,951

6,171

 

Emergency department visits

An average of 1,077,584 emergency department visits for ILIs were recorded each year (range: 312,306-1,644,758), representing 15 % of all emergency visits. Pneumonia was diagnosed in 5.5 % of ILI cases, and 51 % of the patients were female. Children under five years of age accounted for 32.67 % of ILI cases, while individuals over 65 years of age accounted for 7.93 % (Table 4). A total of 51.32 % of emergency department visits for ILIs were registered in services affiliated with EsSalud. Differences were found in rates across departments and years of care (p = 0.01), with the lowest rate recorded in Lambayeque (164 cases per 100,000 inhabitants) and the highest in Moquegua (14,347 cases per 100,000 inhabitants) (Table 2). The estimated annual rates of emergency department visits for ILIs by region showed significant differences between the coast, highlands and jungle (p = 0.01). The highlands recorded the lowest rate of emergency department visits for ILIs in 2020, with 610 cases per 100,000 inhabitants, whereas the coast reported the highest rate in 2018, with 6,883 cases per 100,000 inhabitants. These results are presented in Table 5.

 

Table 2. Number of visits and rates of ILIs in emergency services across departments and years of care

 

 

 

 

 

 

Emergency department visits

 

 

 

 

 

Period

2018

 

2019

 

2020

 

2021

 

2022

 

 

n

Rate

n

Rate

n

Rate

n

Rate

n

Rate

Peru

1,708,727

5,414

1,306,793

4,067

354,187

1,086

797,265

2,413

1,538,493

4,607

Amazonas

5,989

1,427

3,758

887

1,539

361

3,810

889

7,800

1,816

Ancash

60,775

5,260

52,284

4,471

18,494

1,566

32,162

2,706

56,612

4,741

Apurímac

9,831

2,301

6,507

1,515

3,147

731

4,788

1,112

12,777

2,973

Arequipa

169,030

11,831

106,687

7,284

35,239

2,353

64,341

4,214

144,909

9,325

Ayacucho

19,589

2,972

12,522

1,884

2,315

346

13,291

1,984

24,535

3,659

Cajamarca

30,570

2,125

28,740

1,985

2,597

179

7,126

490

11,615

799

Callao

108,084

10,019

84,855

7,676

23,731

2,100

59,836

5,196

119,137

10,168

Cusco

48,448

3,669

45,078

3,363

7,304

538

11,183

816

37,634

2,726

Huancavelica

3,846

1,022

3,911

1,053

1,236

338

3,838

1,071

7,015

1,999

Huánuco

23,673

3,125

15,830

2,083

5,288

696

10,417

1,374

16,954

2,245

Ica

98,427

10,662

75,097

7,904

8,687

891

33,259

3,332

69,677

6,831

Junín

33,542

2,512

27,029

2,002

12,795

940

26,526

1,938

46,498

3,384

La Libertad

73,438

3,788

45,974

2,322

9,111

452

19,557

955

33,871

1,630

Lambayeque

26,334

2,073

12,719

984

2,149

164

3,162

238

13,879

1,037

Lima

792,920

7,789

634,822

6,095

159,134

1,497

314,106

2,905

706,663

6,432

Loreto

37,103

3,709

36,129

3,559

12,145

1,182

35,407

3,414

33,319

3,189

Madre de Dios

4,205

2,607

3,121

1,861

1,779

1,024

5,132

2,856

8,638

4,657

Moquegua

26,738

14,347

18,010

9,490

6,848

3,553

8,632

4,422

16,225

8,222

Pasco

9,476

3,488

5,692

2,091

4,256

1,565

5,875

2,169

9,205

3,418

Piura

31,591

1,600

20,242

1,005

5,872

287

13,248

638

21,896

1,041

Puno

24,852

2,009

15,990

1,291

9,299

751

15,666

1,270

28,372

2,314

San Martín

20,385

2,352

15,904

1,799

7,522

836

70,981

7,777

37,070

4,010

Tacna

27,584

7,778

21,019

5,787

4,098

1,105

7,829

2,072

35,876

9,337

Tumbes

12,055

4,995

7,203

2,920

4,502

1,790

15,042

5,882

13,465

5,188

Ucayali

10,242

1,833

7,670

1,335

5,100

866

12,051

2,000

24,851

4,041

 

 

Hospitalizations

In the Peruvian health system, an average of 56,587 hospitalizations for ILIs were recorded each year (range: 46,338-67,233), representing 2.9 % of all causes of hospitalization. Pneumonia was diagnosed in 79.8 % of ILI cases, and 55 % of the patients were male. Children under five years of age accounted for 23.7 % of hospitalized patients, while individuals over 65 years of age accounted for 32 % (Table 4). A total of 60.6 % of patients hospitalized for ILIs were treated in services affiliated with MINSA. Differences were found in rates across departments and years of care (p = 0.01), with the lowest rate recorded in Tacna (8 cases per 100,000 inhabitants) and the highest in Ica (495 cases per 100,000 inhabitants) (Table 3). The estimated annual rates of hospitalizations for ILIs by region showed significant differences between the coast, highlands and jungle (p = 0.01). The jungle recorded the lowest rate of hospitalizations for ILIs in 2019, with 14 cases per 100,000 inhabitants, whereas the coast reported the highest rate in 2018, with 244 cases per 100,000 inhabitants. These results are presented in Table 5.

 

Table 3.Number of visits and rates of ILIs in hospitalization services across departments and years of care

 

 

 

 

 

 

Hospitalizations

 

 

 

 

 

Period

2018

 

2019

 

2020

 

2021

 

2022

 

 

n

Rate

n

Rate

n

Rate

n

Rate

n

Rate

Peru

67,233

213

7,411

23

46,338

142

65,051

197

47,733

143

Amazonas

1,122

267

58

14

473

111

754

176

538

125

Ancash

1,780

154

175

15

1,866

158

3,434

289

1,463

123

Apurímac

929

217

120

28

696

162

1,295

301

804

187

Arequipa

3,577

250

285

19

2,276

152

2,750

180

2,237

144

Ayacucho

938

142

120

18

809

121

1,660

248

933

139

Cajamarca

1,711

119

244

17

718

49

1,636

112

1,306

90

Callao

2,331

216

406

37

1,454

129

1,525

132

1,359

116

Cusco

2,938

222

280

21

1,199

88

2,722

199

3,313

240

Huancavelica

375

100

61

16

224

61

618

172

525

150

Huánuco

865

114

76

10

769

101

1,412

186

443

59

Ica

2,569

278

759

80

2,504

257

4,939

495

2,621

257

Junín

1,937

145

269

20

1,124

83

1,414

103

1,496

109

La Libertad

3,469

179

480

24

2,112

105

2,270

111

1,869

90

Lambayeque

1,485

117

517

40

794

61

804

61

932

70

Lima

32,209

316

2,441

23

22,882

215

25,737

238

19,124

174

Loreto

894

89

164

16

531

52

1,400

135

1,055

101

Madre de Dios

367

227

41

24

311

179

273

152

339

183

Moquegua

502

269

56

30

375

195

245

126

274

139

Pasco

533

196

73

27

256

94

441

163

240

89

Piura

1,999

101

221

11

1,310

64

1,575

76

1,346

64

Puno

2,206

178

333

27

1,271

103

3,352

272

2,835

231

San Martín

1,131

130

82

9

1,635

182

3,510

385

1,926

208

Tacna

326

92

30

8

63

17

192

51

159

41

Tumbes

281

116

51

21

219

87

364

142

262

101

Ucayali

759

136

69

12

467

79

729

121

334

54

 

 

 

Table 4. Annual range of visits and rates of ILIs across age groups (2018-2022)

 

Age group

ILI cases

 

Outpatient services

 

 

Emergency services

 

 

Hospitalizations services

 

 

 

Outpatient visitis

 

Rate per 100,000 inhabitants

 

Emergency visits

 

Rate per 100,000 inhabitants

 

Hospitalizations

 

Rate per 100,000 inhabitants

 

0 to 4 years

1,770,159

559,876

1,160,632

400,418

42,146

14,338

589,199

74,813

21,396

2,683

24,343

3,116

884

113

5 to 9 years

719,715

137,863

502,754

111,094

17,176

4,280

252,528

25,551

9,566

984

4,975

631

170

22

10 to 14 years

349,340

130,494

291,450

91,563

10,637

3,376

101,160

14,900

3,780

544

1,585

256

57

9

15 to 19 years

193,190

60,929

143,519

50,278

5,350

2,039

55,057

10,280

2,052

417

1,106

113

43

4

20 to 24 years

170,762

69,433

121,996

53,569

4,588

1,990

54,533

15,280

2,051

568

1,400

157

53

6

25 to 29 years

210,783

89,614

143,888

65,325

6,013

2,408

75,964

23,259

2,962

858

1,919

142

70

6

30 to 34 years

233,744

96,549

164,322

69,132

7,379

2,678

81,746

25,867

3,394

1,002

2,958

180

113

8

35 to 39 years

247,512

97,303

167,259

68,736

8,129

2,806

80,369

26,481

3,906

1,081

3,655

137

147

7

40 to 44 years

235,927

91,221

160,657

63,399

8,471

2,824

74,215

25,230

3,913

1,124

4,436

135

194

7

45 to 49 years

211,794

85,890

145,689

59,294

8,662

3,060

65,391

23,679

3,888

1,222

4,786

168

240

10

50 to 54 years

301,214

108,189

277,022

65,451

15,741

3,645

60,726

20,705

4,165

1,176

5,345

161

298

11

55 to 59 years

183,017

72,178

130,228

50,343

10,760

3,318

53,031

18,007

4,382

1,187

5,875

186

376

15

60 to 64 years

160,602

59,594

117,209

41,008

11,571

3,391

46,559

14,577

4,596

1,205

5,574

185

444

18

65 years and older

493,502

162,755

344,292

111,040

15,345

3,788

145,629

35,558

6,491

1,213

22,363

1,844

997

82

 

 

 

Table 5. Number of visits and rates of ILIs in outpatient, emergency and hospitalization services across regions (coast, highlands and jungle) and years of care

 

 

 

 

Period

 

 

 

2018

2019

2020

2021

2022

Outpatient visits

 

 

 

 

 

Coast

 

 

 

 

 

n

2,430,686

2,443,167

637,086

770,486

1,276,618

Rate

11,724

11,529

2,949

3,509

5,728

Highlands

 

 

 

 

 

n

1,016,548

1,111,316

1,050,500

616,171

822,761

Rate

12,995

14,112

13,286

7,784

10,400

Jungle

 

 

 

 

 

n

156,299

155,816

103,235

95,237

195,702

Rate

5,198

5,083

3,312

3,014

6,117

Emergency department visits

 

 

 

 

 

Coast

 

 

 

 

 

n

1,426,976

1,078,912

277,865

571,174

1,232,210

Rate

6,883

5,091

1,286

2,601

5,529

Highlands

 

 

 

 

 

n

203,827

161,299

48,237

98,710

194,605

Rate

2,606

2,048

610

1,247

2,460

Jungle

 

 

 

 

 

n

77,924

66,582

28,085

127,381

111,678

Rate

2,591

2,172

901

4,031

3,491

Hospitalizations

 

 

 

 

 

Coast

 

 

 

 

 

n

50,528

5,421

35,855

43,835

31,646

Rate

244

26

166

200

142

Highlands

 

 

 

 

 

n

12,432

1,576

7,066

14,550

11,895

Rate

159

20

89

184

150

Jungle

 

 

 

 

 

n

4,273

414

3,417

6,666

4,192

Rate

142

14

110

211

131

 

 

 

 

DISCUSSION

This study aims to estimate ILI disease burden within the Peruvian health system. Over the past five years, ILIs have resulted in 7,714 outpatient visits, 3,227 emergency department visits and 169 hospitalizations per 100,000 inhabitants. The highest ILI burden was observed in children under five years of age, aligning with the international literature (5,11). However, comparisons should be made cautiously, as case definitions varied across studies, and in some cases the results from some hospitals were extrapolated to provincial or national levels (12,13). In emergency departments, ILIs accounted for 15 % of all visits.

ILIs (14,16) are highly infectious diseases, estimated to cause three to five million severe cases and 290,000 to 650,000 deaths worldwide each year (17). Annual estimates highlight the continuous evolution of influenza and its seasonal variability, underscoring the importance of using ranges to more accurately reflect its annual burden (18,19).

ILI burden estimates the number of individuals who fall ill and seek care through outpatient, emergency and hospitalization services, or die within a given period (20). The variability of ILIs makes it difficult to assess their overall impact on the health system (21). This study evaluated five years of data, including three years within the COVID-19 pandemic, though these were not considered in our study.

The present study seeks to estimate ILI burden within the Peruvian health system, providing disease-specific burden estimates over the five-year evaluation period. The limitations identified are as follows:

Estimates of visits for ILIs rely on administrative data reported to SUSALUD (22), making them susceptible to biases such as diagnostic coding errors or underreporting, which could affect burden estimates (23).

Healthcare-seeking patterns (24) changed with the onset of the COVID-19 pandemic and its overlap with ILIs, as well as due to the implementation of preventive public health measures such as social distancing and mask use (25) and school closures during the pandemic. These factors likely influenced the dynamics of ILIs.

Another limitation is that ILIs can be caused by various pathogens, both viral and bacterial, while influenza infections can lead to illnesses that do not meet the ILI definition (26,28). This proportion has exceeded 50 % during peak influenza transmission (29).

Despite its limitations, the study provides a straightforward and timely assessment of ILI burden, offering valuable insights into economic and social costs and contributing to public health decision-making (30).

In conclusion, the results of this study demonstrate that ILIs represent a considerable burden for the Peruvian health system. Estimating the annual burden can enhance surveillance efforts for ILIs, assess vaccination impact, improve epidemiological understanding, and strengthen preparedness for future influenza pandemics.

 

BIBLIOGRAPHIC REFERENCES

1.Wang C, Yang Yan-Na, Xi L, Yang L, Du J, Zhang Z, et al. Dynamics of influenza-like illness under urbanization procedure and COVID-19 pandemic in the subcenter of Beijing during 2013- 2021. J Med Virol &#091;Internet&#093;. 2022;94(8):3801-10.

2.Savy V, Ciapponi A, Bardach A, Glujovsky D, Aruj P, Mazzoni A, et al. Burden of influenza in Latin America and the Caribbean: a systematic review and meta-analysis. Influenza Other Respir Viruses &#091;Internet&#093;. 2013;7(6):1017-32.

3.Rolfes MA, Foppa IM, Garg S, Flannery B, Brammer L, Singleton JA, et al. Annual estimates of the burden of seasonal influenza in the United States: a tool for strengthening influenza surveillance and preparedness. Influenza Other Respir Viruses &#091;Internet&#093;. 2018;12(1):132-7.

4.Cowling BJ, Ali ST, Ng TWY, Tsang TK, Li JCM, Fong MW, et al. Impact assessment of non-pharmaceutical interventions against coronavirus disease 2019 and influenza in Hong Kong: an observational study. Lancet Public Health &#091;Internet&#093;. 2020;5(5):e279-88.

5.Lee K, Jalal H, Raviotta JM, Krauland MG, Zimmerman RK, Burke DS, et al. Estimating the impact of low influenza activity in 2020 on population immunity and future influenza seasons in the United States. Open Forum Infect Dis &#091;Internet&#093;. 2022;9(1):ofab607.

6.Tsang TK, Huang X, Guo Y, Lau EHY, Cowling BJ, Ip DKM. Monitoring school absenteeism for influenza-like illness surveillance: systematic review and meta-analysis. JMIR Public Health Surveill &#091;Internet&#093;. 2023;9:e41329.

7.Alcalde-Rabanal JE, Lazo-González O, Nigenda G. Sistema de salud de Perú. Salud Publica Méx &#091;Internet&#093;. 2011;53(2):243-54.

8.SUSALUD. Búsqueda de datos abiertos &#091;Internet&#093;. Lima: Superintendencia Nacional de Salud; 2023. Available from: http:// datos.susalud.gob.pe/

9.World Health Organization. ICD-10 Version:2019 &#091;Internet&#093;. Ginebra: World Health Organization; 2019. Available from: https:// icd.who.int/browse10/2019/en

10.MINSA. Directiva sanitaria N° 061-minsa/dge v.01 &#091;Internet&#093;. Lima: Dirección general de Epidemiología; 2015. Available from: https:// bvs.minsa.gob.pe/local/MINSA/3266.pdf

11.Darmaa O, Burmaa A, Gantsooj B, Darmaa B, Nymadawa P, Sullivan S, et al. Influenza epidemiology and burden of disease in Mongolia, 2013-2014 to 2017-2018. Western Pac Surveill Response J &#091;Internet&#093;. 2021;12(2):28-37.

12.Yu H, Huang J, Huai Y, Guan X, Klena J, Liu S, et al. The substantial hospitalization burden of influenza in central China: surveillance for severe, acute respiratory infection, and influenza viruses, 2010- 2012. Influenza Other Respir Viruses &#091;Internet&#093;. 2014;8(1):53-65.

13.Dawa JA, Chaves SS, Nyawanda B, Njuguna HN, Makokha C, Otieno NA, et al. National burden of hospitalized and non- hospitalized influenza-associated severe acute respiratory illness in Kenya, 2012-2014. Influenza Other Respir Viruses &#091;Internet&#093;. 2018;12(1):30-7.

14.Barahona G, Dueñas M, Pleites E. Infecciones por el virus de la influenza. Medicine &#091;Internet&#093;. 2022;13(58):3392-7.

15.Lyons DM, Lauring AS. Mutation and epistasis in influenza virus evolution. Viruses &#091;Internet&#093;. 2018;10(8):407.

16.Poon LLM, Song T, Rosenfeld R, Lin X, Rogers MB, Zhou B, et al. Quantifying influenza virus diversity and transmission in humans. Nat Genet &#091;Internet&#093;. 2016;48(2):195-200.

17. Iuliano AD, Roguski KM, Chang HH, Muscatello DJ, Palekar R, Tempia S, et al. Estimates of global seasonal influenza-associated respiratory mortality: a modelling study. The Lancet &#091;Internet&#093;. 2018;391(10127):1285-300.

18.Paget J, Spreeuwenberg P, Charu V, Taylor RJ, Iuliano AD, Bresee J, et al. Global mortality associated with seasonal influenza epidemics: new burden estimates and predictors from the GLaMOR Project. J Glob Health &#091;Internet&#093;. 2019;9(2)020421.

19.Barriga Reyes NM, López Londo AJ, Chávez Almeida JF, Galarza Galarza JG. Influenza: updating of cepas. RECIAMUC &#091;Internet&#093;. 2019;3(3): 595-625.

20.World Health Organization. A manual for estimating disease burden associated with seasonal influenza &#091;Internet&#093;. Ginebra: World Health Organization; 2015. Available from: https://www. who.int/publications/i/item/9789241549301

21.Sánchez-Moreno F. El sistema nacional de salud en el Perú. Rev Peru med Exp Salud Pública &#091;Internet&#093;. 2014;31(4):747-53.

22.Quijano-Caballero O, Munares-García O. Protección de derechos en salud en el Perú: Experiencias desde el rol fiscalizador de la Superintendencia Nacional de Salud. Rev Peru Med Exp Salud Pública &#091;Internet&#093;. 2016;33(3):529-34.

23.Mejía-Santos HM, Couto P, Palekar R, Molina JA, Urbina GA, Daza- Vergara JA, et al. Hospitalizaciones y mortalidad asociada a influenza, Honduras. 2011-2015. Rev. Fac Cienc Méd &#091;Internet&#093;. 2019;16(2):11-22.

24.Cabezas C. Atención médica y de salud en el Perú. Rev Peru Med Exp Salud Pública &#091;Internet&#093;. 2019;36(2):165-6.

25.Laguna-Torres VA. Infecciones emergentes y remergentes. Infecciones por el virus de la influenza. Diagnóstico &#091;Internet&#093;. 2013;52(1).

26.Biggerstaff M, Jhung M, Kamimoto L, Balluz L, Finelli L. Self- reported influenza-like illness and receipt of influenza antiviral drugs during the 2009 pandemic, United States, 2009-2010. Am J Public Health &#091;Internet&#093;. 2012;102(10): e21-6.

27.Woo PCY, Lau SKP, Chu Chung-ming, Chan Kwok-hung, Tsoi Hoi- wah, Huang Y, et al. Characterization and complete genome sequence of a novel Coronavirus, Coronavirus HKU1, from patients with pneumonia. J Virol &#091;Internet&#093;. 2005;79(2):884-95.

28.Centro para el control y la prevención de las enfermedades. Datos claves sobre la influenza &#091;Internet&#093;. Estados Unidos: CDC; 2022. Available from: https://espanol.cdc.gov/flu/about/keyfacts.htm

29.Ren L, Gonzalez R, Wang Z, Xiang Z, Wang Y, Zhou H, et al. Prevalence of human respiratory viruses in adults with acute respiratory tract infections in Beijing, 2005-2007. Clin Microbiol Infect &#091;Internet&#093;. 2009;15(12):1146-53.

30.Epstein D, Negrín Hernández MA, Bermúdez Tamayo C, Cantarero Prieto D, Álvarez-Dardet C. Toma de decisiones en salud pública basada en la evidencia: número temático en Gaceta Sanitaria. Gac Sanit &#091;Internet&#093;. 2020;34(4):316-7.

 

 

Author contributions: WEPL conceived, designed and wrote the manuscript, and also approved its final version. Additionally, WEPL and MVCHR performed the required statistical analyses and critically reviewed the contents.

Funding sources: The article was funded by the authors.

Conflicts of interest: The authors declare no conflicts of interest.

 

Corresponding author:

Walter Enrique Prudencio León

Address: Avenida Andrés Aramburú cuadra 2 s/n, Miraflores. Lima, Perú.

Telephone: +51 999 671 847

E-mail: wpl29@hotmail.com

 

Reception date: December 20, 2023

Evaluation date: February 19, 2024

Approval date: February 28, 2024