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
11
12
13
. 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; X2 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 (X2), 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.
<p>Table 1</p>
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(m
2
) (X5)
No. of ITNs (X6)
#2.5% Cyhalothrin.
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
<p>Figure 1</p>Relationship of malaria incidence and malaria prevention and control measures in Hainan Province, China from 2001 to 2013
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).
<p>Table 2</p>
The correlation analysis of malaria incidence with socio-economic development in Hainan Province
Years
(Y0)
(Y1)
(Y2)
(Y3)
(Y4)
(Y5)
(Y6)
(Y7)
(Y8)
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).
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
<p>Figure 2</p>Relationship between socio-economic development and incidence of malaria in Hainan Province, China, 2001–2013
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
22
23
24
. 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
26
27
28
29
. 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.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
SW, YL, ZZ, GW, and XH were involved in the conceptualization, design, execution, and first draft of the manuscript. RDX and WAQ contributed to consulting, data analysis and interpretation of the results. All authors were involved in the preparation of the manuscripts. All authors read and approved the final manuscript.