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  • Open Access

Prevention measures and socio-economic development result in a decrease in malaria in Hainan, China

Malaria Journal201413:362

https://doi.org/10.1186/1475-2875-13-362

  • Received: 6 June 2014
  • Accepted: 28 August 2014
  • Published:

Abstract

Background

Historically, the incidence of malaria in the Hainan Province, China has been high. However, since 2001 the malaria incidence in Hainan has decreased due to large-scale, public educational, promotional campaigns and the adoption of preventative measures against malaria following the fast growth of socio-economic development. The present study analysed the correlation between prevention measures and social economic development on the incidence of malaria in Hainan from 2001 to 2013.

Methods

The data of malaria preventative measures and socio-economic development were collected from various cities and counties in Hainan Province from 2001 to 2013 and analysed by the grey correlation analysis system.

Results

Seasonal preventive medication and local fiscal revenue increases are significantly related to the reduction of malaria incidence from 2001 to 2013 (R1 = 0.751677; R5 = 0.764795).

Conclusion

Malaria prevention and control measures and local economic development in Hainan decreased malaria incidence from 2001 to 2013.

Keywords

  • Malaria
  • Integrated vector management
  • Malaria preventative medication
  • Grey correlation

Background

Hainan Island is located in the southern part of China, with northern latitude 18°10′ ~ 20°10′, and eastern longitude 108°37′ ~ 111°03′. It has a population of 8.54 million, among which 83% are Han nationality, where 17% are minority. Hainan Island covers an area of 34 thousand square kilometer. Mountains and hills covering 38.7% of the area, mainly located at south central Island, are the main terrain of Hainan Island. The Island has an average temperature of 23.4 - 26.5°C, with annual precipitation of 1437.0 – 3022.7 mm and annual daylight duration of 1573.5 – 2443.4 hours. Weather and environment are suitable for breeding of the malarial vectors, like Anopheles dirus and Anopheles minimus.

Malaria has been reduced dramatically in China as a result of unprecedented governmental and international organizational efforts. Thirty million malaria cases were reported in 1949 in the People’s Republic of China, which has since been dramatically decreased to 1,314 cases in 2011 [1, 2]. In addition, during the same time, the epidemiological counts were decreased proportionally from 1,829 to 353 [3]. Hainan Province, located in the south of China, was one of the most important endemic malaria areas, with a high transmission of Plasmodium falciparum and Plasmodium vivax. Hainan implemented unprecedented measures for controlling malaria, such as mass drug administration (MDA) [4], long-lasting insecticide-treated mosquito nets (LLINs) [5], artemisinin-based combination therapy (ACT) [6], radical treatment [7], indoor residual spraying (IRS) [8], and chemoprophylaxis [9]. These methods have proven effective for controlling and preventing malaria transmission and there is no local- acquired case of P. falciparum reported in Hainan since 2009 [3].

In China, comprehensive prevention measures, including controlling malaria vectors and treating patients, were strongly encouraged and applied in the field with successful progress [10]. However, it is unclear which of the comprehensive measures implemented for controlling malaria were more effective. Statistical models, such as a logistic relation model, a negative binomial model, and a join point regress model have been applied to analyse the relationship between the incidence of malaria and climate, control measures and economic factors [1113]. Grey relational analysis (GRA), is a useful tool for the selection of optimized factors from multiple performance characteristics, and has been applied in the field of engineering [14, 15]. GRA models are derived from the grey system theory and used as a method for analysing relationship between outcomes and factors. GRA has gradually been applied to clinical evaluation, socio-economic and natural factors on the influence of malaria epidemics and experimental studies [16, 17].

In this paper, the GRA method was used to make a comprehensive evaluation of the relationship between the incidence of malaria, human interventions in relation to malaria prevention and prevention measures following socio-economic development in Hainan, China.

Methods

Data resource and collection

Data were compiled from reports by the Ministry of Health and Malarial Control and Research in Hainan Province (2000–2013) on malaria incidence, the administration of primaquine, preventative measures in endemic seasons, the size of residual spraying areas, and the number of LLINs distributed [18]; collected from the Hainan Yearbook [19] were: socio- economic development of Hainan Province’s gross domestic product (GDP), GDP per capita of Hainan Province, the provincial agricultural population, the number of rural laborers, the local finance income, per capita net income of rural households, rural residents, and rural health care spending per capita housing area.

Analysis method

The grey correlation analysis software GM (grey system theory and application of the third edition) was used [20].

To facilitate the analysis, the mean dimensionless processing model was used to sequence the comparison between the different dimensions and orders of magnitude. The formula below was applied:
ξ i k = m in i Δ i m in + 0.5 m ax i Δ i m a x x 0 k x i k + 0.5 m ax i Δ i m a x

where K is the correlation coefficient representing the moment curve and the relative difference between the reference curve. Among the curves, the coefficient of 0.5 is used to distinguish between 0 and 1 of the general selection [21].

GRA uses the incidence of a disease (1/10,000) for the associated factors (X0/Y0); X1 represents the number of preventive medicine strategies; X 2 represents preventive medication dose rate (%); X3 represents the resting phase effect on a radical cure medication number; X4 represents the resting phase effect on a radical cure medicine suit ratio (%); X5 represents the retention area (sq m) of the insecticide spray path (IRS); X6 represents LLINs. The social development factors, in order: Y1 represents Hainan Province (100 million yuan); Y2 represents GDP per capita; Y3 represents the provincial agricultural population (10,000); Y4 represents rural laborers (10,000); Y5 represents the local fiscal revenue (10,000 yuan); Y6 represents the per capita net income of rural households; Y7 represents the rural residents’ health care expenditure; and, Y8 represents the rural per capita housing area (sq m). Data from 2001–2013 were entered into a computer software operating system item by item and the indices of correlation between the correlation factors and associated factors were conducted.

Results

Control measures and the incidence

The result showed that the control measures used were significantly related to the malaria incidence in Hainan Province, China (r1 = 0.751677, r2 = 0.60305, r3 = 0.628916, r4 = 0.563998, r5 = 0.615526, r6 = 0.661795) (Table 1). The comprehensive preventative measures are ranked according to the significant impacts on malaria incidence reduction: preventative medicine (X1), radical medication (X3), LLINs (X6), IRS area (X5), prevention medicine dose rate (X 2), and radical medicine suit ratio (X4) (Figure 1). During the ten-year period, a popular seasonal preventive medication provided to the people of Hainan had the most significant relationship with the reduction of malaria incidence.
Table 1

The correlation analysis of malaria incidence, malaria prevention and control measures

Years

Incidence

Preventive medicine (PM)

Radical treatment (RT)

Insecticides#

(1/10,000) (X0)

No. of PM (X1)

% of PM ( X 2)

No. of RT (X3)

% of finish RT (X4)

Area of IRS(m2) (X5)

No. of ITNs (X6)

2001

5.95

23,202

95.78

17,162

96.6

642,031

29,717

2002

6.92

27,725

96.5

28,903

93.01

0

26,669

2003

7.84

20,093

95.16

26,538

97.42

988,165

31,098

2004

11.52

6,504

96.21

10,026

99.68

869,996

57,551

2005

5.46

29,239

96.69

25,109

98.65

506,935

58,624

2006

4.66

122,024

93.04

44,203

98.88

1,049,305

55,188

2007

4.09

28,646

91.3

30,263

99.05

248,425

177,742

2008

2.21

30,818

94.16

55,091

98.79

1,257

162,064

2009

0.79

35,811

96.2

57,048

98.74

282,908

158,541

2010

0.09

12,850

94.15

17,571

97.89

470,701

138,548

2011

0.01

7,726

98.91

4,791

97.58

262,295

71,941

2012

0

415

96.26

1,143

93.16

730,452

47,356

2013

0

1,132

99.76

22

100

117,954

19,083

Correlation coefficient

0.7917

0.5527

0.7000

0.5389

0.6032

0.6592

#2.5% Cyhalothrin.

Figure 1
Figure 1

Relationship of malaria incidence and malaria prevention and control measures in Hainan Province, China from 2001 to 2013.

Socio-economic development and malaria incidence

The results showed that socio-economic development in Hainan Province was significantly related to malaria incidence (r1 = 0.676872, r2 = 0.666447, r3 = 0.64267, r4 = 0.598968, r5 = 0.764795, r6 = 0.645387, r7 = 0.586146, r8 = 0.635062) (Table 2).Socio-economic development has associations with the reduction of malaria incidence: local fiscal revenue (Y5) > Hainan Province revenue (Y1) > GDP per capita (Y2) > per capita net income of rural households (Y6) > rural per capita housing area (Y8) > rural resident health care expenditure (Y7) > provincial agricultural population (Y3) > rural laborers (Y4) (Figure 2).
Table 2

The correlation analysis of malaria incidence with socio-economic development in Hainan Province

Years

(Y0)

(Y1)

(Y2)

(Y3)

(Y4)

(Y5)

(Y6)

(Y7)

(Y8)

2001

5.95

579.17

7,315

567.19

229.53

495,924

2,285

39.1

19.61

2002

6.92

642.73

8,041

570.43

233.53

518,324

2,423

62.23

19.16

2003

7.84

713.96

8,849

574.9

240.27

615,971

2,588

96.05

19.51

2004

11.52

819.66

10,067

501.15

250.04

692,965

2,818

86.57

19.92

2005

5.46

918.75

11,165

505.3

256.01

848,930

3,004

93.00

21.82

2006

4.66

1,065.67

12,810

512.07

259.87

1,023,508

3,256

110.92

22.05

2007

4.09

1,254.17

14,923

521.39

269.28

1,524,579

3,791

95.55

22.64

2008

2.21

1,503.06

17,691

529.76

274.6

2,297,559

4,390

123.82

22.84

2009

0.79

1,654.21

19,254

539.31

281.59

2,996,659

4,744

129.26

24.00

2010

0.09

2,064.5

23,831

552.63

284.58

5,516,154

5,275

138.35

24.74

2011

0.01

2,515.29

28,797

434.3

225.18

6,898,400

6,446

175.52

25.35

2012

0

2,855.26

32,374

457.45

237.19

7,708,700

7,408

201.72

26.12

2013

0

3,146.46

35,317

423.11

219.38

8,211,000

8,343

227.18

26.59

Correlation coefficient

0.6551

0.6479

0.5879

0.5490

0.7073

0.6420

0.6079

0.6405

 

Note: Y0-Incidence (1/10,000); Y1-GDP (100 million yuan); Y2- Real GDP per capita (yuan); Y3- Agricultural population (10,000); Y4- Rural workers (10,000); Y5- Local fiscal revenue (10,000 yuan); Y6- Per capita net income of rural households (yuan); Y7- Rural residents’ healthcare expenditure (yuan); Y8- Rural per capita housing area (sq m).

Figure 2
Figure 2

Relationship between socio-economic development and incidence of malaria in Hainan Province, China, 2001–2013.

Discussion

In 2010, the Chinese government decided to embark upon the national malaria elimination program (NMEP), with the goal of eliminating malaria by 2015 in the majority of China with the exception of the border region of Yunnan Province. In addition, the goal of elimination in the People’s Republic of China was set for 2020. Furthermore, the Action Plan of China Malaria Elimination (2010–2020) (APCME) was issued by the Chinese government [10]. According to APCME standards, there were ten counties of high malaria incidence in Hainan Province.

The major factors used to reduce malaria incidence were the promotion and administration of preventative medicines, primarily primaquine, and the distribution of LLINs before the start of malaria transmission in endemic regions. The small correlation between the ratio of completed courses of radical medical treatment and the incidence of malaria in this study may suggest that it is also necessary to administer anti-malarial drugs. Recent progress in malaria control has renewed enthusiasm and interest in MDA as a potential strategy for elimination and eradication [2224]. MDA has also been considered as a strategy to contain the recent emergence of artemisinin resistance in the Cambodia-Thai and Thai-Myanmar borders and Jiangsu Province [10, 24, 25].

The combination of anti-malarial drugs and LLINs have been followed by reports of a decline in transmission of malaria in South Africa, Thailand, Rwanda, Ethiopia, and Zanzibar [2629]. In China, deltamethrin-treated LLINs have reduced the density of indoor Anopheles minimus, a main vector in high malaria areas on Hainan Island, and reduced indoor mosquito-parasite transmission, but have not affected malaria transmission outdoors [30, 31].

Pesticide residual spraying of an area was found to have little association with the decrease in the incidence of malaria. This relationship may be caused by the broad impact of preventative and curative measures and the lack of integrated vector management strategies available in Hainan [30]. In Kenya the effect of both IRS and Bacillus-based larvicides reduced malaria transmission and the number of clinical malaria cases in 2010 and 2011 [32]. The feasibility of IRS malaria control in Hainan Province needs to be studied further due to the influences of indoor and outdoor resting behaviors of the major vector mosquito, An. minimus.

Socio-economic development has a close relationship with people’s physical health; it influences malaria incidence within the populations. According to the calculation, the results showed that the local fiscal revenue is significantly related to the malaria incidence, followed by GDP in Hainan. Socio-economic development has increased local fiscal revenue and improved farmers’ living conditions. This has directly reduced breeding sites for vector mosquitoes and drastically reduced the incidence of malaria. However, since there was little correlation between expenditure of rural residents and malaria incidence, this may indicate that farmers have not paid enough for medical care or healthcare expenses related to malaria treatment.

In addition to control and prevention measures, improving social and economic conditions, especially for ethnic minorities and in remote rural areas, is essential for malaria elimination in Hainan. The establishment of a network of medical treatment which provides a combination of malaria prevention and control along with basic public health services is necessary; promotion of health education and healthcare awareness are priorities for malaria control for minority groups in remote areas of Hainan Province, China [33, 34].

Conclusion

The promotion of preventative measures through the administration of anti-malarial drugs, LLINs and radical treatment medication have benefited malaria control in Hainan Province, China. Socio-economic development, such as local and provincial economic growth and improved health conditions, have significantly reduced malaria incidence in Hainan Province, China from 2001 to 2013.

Abbreviations

ACT: 

Artemisinin-based combination therapy

GDP: 

Gross domestic product

GRA: 

Grey relational analysis

IRS: 

Indoor residual spraying

LLINS: 

Long-lasting, insecticide-treated mosquito nets

MDA: 

Mass drug administration

NMEP: 

National malaria elimination program

APCME: 

Action plan of China malaria elimination.

Declarations

Acknowledgements

This study received financial support from the Hainan Provincial Scientific Research grant (Grant No 813251). Our thanks go to W D Gu, J M Scott, A Fulcher, and K Lizzi for reviewing/editing the manuscript.

Authors’ Affiliations

(1)
Hainan Provincial Centre for Disease Control and Prevention, Haikou, 570203, China
(2)
Haikou Centre for Disease Control and Prevention, Haikou, 571100, China
(3)
Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, USA
(4)
Anastasia Mosquito Control District, St Augustine, FL, USA

References

  1. Tang LH: [Achievements in the research on the prevention and treatment of malaria in China](in Chinese). Zhong Guo Ji Sheng Chong Xue Yu Ji Sheng Chong Bing Za Zhi. 1999, 17: 257-259.Google Scholar
  2. Tang LH: [Malaria in China: from control to elimination] (in Chinese). Guo Ji Yi Xue Ji Sheng Chong Bing Za Zhi. 2009, 36: 8-Google Scholar
  3. Yin JH, Yang MN, Zhou SS, Wang Y, Feng J, Xia ZG: Changing malaria transmission and implications in China towards national malaria elimination program between 2010 and 2012. PLoS One. 2013, 8: e74228-10.1371/journal.pone.0074228. doi:10.1371/journal.pone.0074228PubMed CentralView ArticlePubMedGoogle Scholar
  4. Hotez PJ: Mass drug administration and integrated control for the world’s high prevalence neglected tropical diseases. Clin Pharmacol Ther. 2009, 85: 659-664. 10.1038/clpt.2009.16.View ArticlePubMedGoogle Scholar
  5. Guillet P, Alnwick D, Cham MK, Neira M, Zaim M, Heymann D, Mukelabai K: Long-lasting treated mosquito nets: a breakthrough in malaria prevention. Bull World Health Organ. 2001, 79: 998-PubMed CentralPubMedGoogle Scholar
  6. Nosten F, White NJ: Artemisinin-based combination treatment of falciparum malaria. Am J Trop Med Hyg. 2007, 77 (Suppl 6): 181-192.PubMedGoogle Scholar
  7. Faucher JF, Bellanger AP, Chirouze C, Hustache-Mathieu L, Genton S, Hoen B: Primaquine for radical cure of Plasmodium vivax and Plasmodium ovale malaria: an observational survey (2008–2010). J Travel Med. 2013, 20: 134-136. 10.1111/jtm.12009.View ArticlePubMedGoogle Scholar
  8. Pluess B, Tanser FC, Lengeler C, Sharp BL: Indoor residual spraying for preventing malaria. Cochrane Database Syst Rev. 2010, Art. No.: CD006657. doi:10.1002/14651858.CD006657.pub2, 4View ArticleGoogle Scholar
  9. Jeong S, Yang HW, Yoon YR: Evaluation of the efficacy of chloroquine chemoprophylaxis for vivax malaria among Republic of Korea Military Personnel. Parasitol Intern. 2013, 62: 494-496. 10.1016/j.parint.2013.07.002.View ArticleGoogle Scholar
  10. Ministry of Health of China: Action Plan of China Malaria Elimination. 2010–2020, Beijing, China: Ministry of Health of China’s Press, in ChineseGoogle Scholar
  11. Zhang WY, Wang LP, Fang LQ, Ma JQ, Xu YF, Jiang JF, Hui FM, Wang JJ, Liang S, Yang H, Cao WC: Spatial analysis of malaria in Anhui province, China. Malar J. 2008, 7: 206-10.1186/1475-2875-7-206.PubMed CentralView ArticlePubMedGoogle Scholar
  12. Hsiang MS, Hwang J, Tao AR, Liu YB, Bennett A, Shanks GD, Cao J, Kachur SP, Feachem RGA, Gosling RD, Gao Q: Mass drug administration for the control and elimination of Plasmodium vivax malaria: an ecological study from Jiangsu province, China. Malar J. 2013, 12: 383-10.1186/1475-2875-12-383.PubMed CentralView ArticlePubMedGoogle Scholar
  13. Alexander N, Moyeed R, Stander J: Spatial modeling of individual-level parasite counts using the negative binomial distribution. Biostatistics. 2000, 1: 453-463. 10.1093/biostatistics/1.4.453.View ArticlePubMedGoogle Scholar
  14. Kuo YY, Yang TH, Huang GW: The use of grey relational analysis in solving multiple attribute decision-making problems. Comput Indust Eng. 2008, 55: 8055E-View ArticleGoogle Scholar
  15. Huang SJ, Chiu NH, Chen LW: Integration of the grey relational analysis with genetic algorithm for software effort estimation. Europ J Operat Res. 2008, 188: 898ERLI-10.1016/j.ejor.2007.07.002.View ArticleGoogle Scholar
  16. Luo FZ, Han YH, Li ST: [Large-scale complicated project strategic alliance partner selection—based on the combination of empowerment grey correlation evaluation](In Chinese). Technoeconom Manag Res. 2013, 1: 8-11.Google Scholar
  17. Zhang ZX, Bi Y: [Primary analysis of relative degree of gray system on malaria incidence and antimalarial measures](In Chinese). J Pract Parasit Dis. 1998, 6: 116-117.Google Scholar
  18. Wang SQ, Du JW, Hu XM: [Research On Malaria Prevention And Treatment In Hainan Province](In Chinese), Volume 6. 2012, Hainan Publishing House, 148-159. 180–205, 1Google Scholar
  19. The people’s Government of Hainan Province: [Hainan Yearbook (2001–2013). (In Chinese). Haikou, Hainan, China: Government of Hainan Province’s PressGoogle Scholar
  20. Liu SF: [The Grey System Theory And Its Application. (In Chinese). 2011, Beijing: Science PressGoogle Scholar
  21. Liu XH: [The spectrum efficiency on immunity from the impact of Astragalus membranaceus study] (in Chinese). J Chin Herbal Med. 2012, 35: 1978-1981.Google Scholar
  22. The maIERA Consultative Group on Drug: A research agenda for malaria eradication: drugs. PLoS Med. 2011, 8: e1000402-View ArticleGoogle Scholar
  23. Cotter C, Sturrock HJW, Hsiang MS, Liu J, Phillips AA, Hwang J, Smith-Gueye C, Fullman N, Gosling RD, Feachem RGA: The changing epidemiology of malaria elimination: new strategies for new challenges. Lancet. 2013, 382: 900-911. 10.1016/S0140-6736(13)60310-4.View ArticlePubMedGoogle Scholar
  24. Maude RJ, Socheat D, Nguon C, Saroth P, Dara P, Li GQ, Song JP, Yeung S, Donforp AM, Day NP, White NJ, White LJ: Optimizing strategies for Plasmodium falciparum malaria elimination in Cambodia: primaquine, mass drug administration and artemisinin resistance. PLoS One. 2012, 7: e37166-10.1371/journal.pone.0037166. doi:10.1371/journal.pone.0037166PubMed CentralView ArticlePubMedGoogle Scholar
  25. World Health Organization: Consideration of mass drug administration for the containment of artemisinin-resistant malaria in the Greater Mekong subregion, Report of a consensus meeting, 27–28 September 2010. 2011, Geneva, Switzerland: World Health OrganizationGoogle Scholar
  26. Barnes KI, Durrheim DN, Little F, Jackson A, Mehta U, Allen E, Dlamini SS, Tsoka J, Bredenkamp B, Mthembu DJ, White NJ, Sharp BL: Effect of artemether-lumefantrine policy and improved vector control on malaria burden in KwaZulu–Natal, South Africa. PLoS Med. 2003, 2: e330-doi:10.1371/journal.pmed.0020330View ArticleGoogle Scholar
  27. Nosten F, Van Vugt M, Price R, Luxemburger C, Thway KL, Brockman A, McGready R, ter Kuiye F, Looareesuwan S, White NJ: Effects of artesunate-mefloquine combination on incidence of Plasmodium falciparum malaria and mefloquine resistance in western Thailand: a prospective study. Lancet. 2000, 356: 297-302. 10.1016/S0140-6736(00)02505-8.View ArticlePubMedGoogle Scholar
  28. Otten M, Aregawi M, Were W, Karema C, Medin A, Bekele W, Jima D, Gausi K, Komatsu R, Korenromp E, Lowbear D, Grabowsky M: Initial evidence of reduction of malaria cases and deaths in Rwanda and Ethiopia due to rapid scale-up of malaria prevention and treatment. Malar J. 2009, 8: 14-10.1186/1475-2875-8-14.PubMed CentralView ArticlePubMedGoogle Scholar
  29. Bhattarai A, Ali AS, Kachur SP, Martensson A, Abbas AK, Khatib R, Al-mafazy A, Ramsan M, Rotllant G, Gerstenmaier JF, Molteni F, Abdulla S, Montgomery SM, Kaneko A, Bjokman A: Impact of artemisinin-based combination therapy and insecticide-treated nets on malaria burden in Zanzibar. PLoS Med. 2007, 4: e309-10.1371/journal.pmed.0040309. doi:10.1371/journal.pmed.0040309PubMed CentralView ArticlePubMedGoogle Scholar
  30. Zhang ZX: [The effect control of Anopheles minimus and Anopheles sinensis by deltamethrin treatment nets](In Chinese). Chin J Parasit Dis Control. 1991, 4: 257-Google Scholar
  31. Wang WM: Jiangsu malaria prevention of grey relation analysis (In Chinese). J Practl Parasit Dis. 1996, 4: 107-Google Scholar
  32. Zhou G, Afrane YA, Dixit A, Atieli HE, Lee MC, Wanjala CL, Beihe LB, Githeko AK, Yan G: Modest additive effects of integrated vector control measures on malaria prevalence and transmission in western Kenya. Malar J. 2013, 12: 256-10.1186/1475-2875-12-256.PubMed CentralView ArticlePubMedGoogle Scholar
  33. Gu ZC, Deng D, Tang LH: [Grey correlation analysis on social factors and malaria endemic](In Chinese). Zhong Guo Ji Sheng Chong Xue Yu Ji Sheng Chong Bin Za Zhi. 1993, 11: 108-110.Google Scholar
  34. He CH, Hu XM, Wang GZ, Zhao W, Sun DW, Li YC, Chen CX, Du JW, Wang SQ: Eliminating Plasmodium falciparum in Hainan, China: a study on the use of behavioral change communication intervention to promote malaria prevention in mountain worker populations. Malar J. 2014, 13: 273-10.1186/1475-2875-13-273.PubMed CentralView ArticlePubMedGoogle Scholar

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© Wang et al.; licensee BioMed Central Ltd. 2014

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