Open Access

Knowledge on the transmission, prevention and treatment of malaria among two endemic populations of Bangladesh and their health-seeking behaviour

  • Syed Masud Ahmed1Email author,
  • Rashidul Haque2,
  • Ubydul Haque2 and
  • Awlad Hossain1
Malaria Journal20098:173

https://doi.org/10.1186/1475-2875-8-173

Received: 12 March 2009

Accepted: 29 July 2009

Published: 29 July 2009

Abstract

Background

Data on sociological and behavioural aspects of malaria, which is essential for an evidence-based design of prevention and control programmes, is lacking in Bangladesh. This paper attempts to fill this knowledge gap by using data from a population-based prevalence survey conducted during July to November 2007, in 13 endemic districts of Bangladesh.

Methods

A two-stage cluster sampling technique was used to select study respondents randomly from 30 mauzas in each district for the socio-behavioural inquiry (n = 9,750). A pre-tested, semi-structured questionnaire was used to collect data in face-to-face interview by trained interviewers, after obtaining informed consent.

Results

The overall malaria prevalence rate in the 13 endemic districts was found to be 3.1% by the Rapid Diagnostic Test 'FalciVax' (P. falciparum 2.73%, P. vivax 0.16% and mixed infection 0.19%), with highest concentration in the three hill districts (11%). Findings revealed superficial knowledge on malaria transmission, prevention and treatment by the respondents. Poverty and level of schooling were found as important determinants of malaria knowledge and practices. Allopathic treatment was uniformly advocated, but the 'know-do' gap became especially evident when in practice majority of the ill persons either did not seek any treatment (31%) or practiced self-treatment (12%). Of those who sought treatment, the majority went to the village doctors and drugstore salespeople (around 40%). Also, there was a delay beyond twenty-four hours in beginning treatment of malaria-like fever in more than half of the instances. In the survey, gender divide in knowledge and health-seeking behaviour was observed disfavouring women. There was also a geographical divide between the high endemic south-eastern area and the low-endemicnorth-eastern area, the former being disadvantaged with respect to different aspects of malaria studied.

Conclusion

The respondents in this study lacked comprehensive knowledge on different aspects of malaria, which was influenced by level of poverty and education. A gender and geographical divide in knowledge was observed disfavouring women and south-eastern area respectively. They preferred allopathic treatment for malaria, although a substantial proportion did not seek any treatment or sought self-treatment for malaria-like fever. Delay in seeking care was common. The implications of these findings for programme development are discussed.

Background

Malaria is a public health problem in some ninety countries worldwide including Bangladesh and estimated to be responsible directly for about 3,000 deaths a day worldwide [1]. The poor and vulnerable populations are disproportionately affected by malaria and the severe consequences of malaria are borne more by the poorest [2]. There is also strong evidence that the use of preventive and treatment interventions for malaria depends upon socio-economic status (SES) [35]. The economic burden of ill health, such as malaria, on individual households can be substantial and in some cases catastrophic, especially for the poor households [6]. Prevention and control of malaria thus can contribute towards poverty alleviation efforts in Bangladesh.

In Bangladesh, the National Malaria Control and Prevention Programme is currently being implemented by the Malaria and Parasitic Disease Control (M&PDC) unit of the Directorate General of Health Services (DGHS), Government of Bangladesh [7, 8]. M&PDC implements the programme in the community in partnership with a BRAC-led consortium of 20 small NGOs (selected through competitive bidding) under funding from GFATM round 6 [8]. BRAC, an indigenous micro-credit/micro-finance-based NGO, is working with the twin objectives of alleviation of poverty and empowerment of the poor [9]. As part of its efforts to mitigate the income-erosion consequences of illnesses for the poor households, BRAC is involved in malaria control activities in the three high endemic hill tracts districts since 1998. This current five-year programme (2007–2012) implemented in all of the 13 endemic districts has both preventive (distribution of LLIN/ITNs, intermittent insecticide residual spray and awareness building programmes) and curative (presumptive case management, early diagnosis and prompt treatment following WHO guidelines, and referral of complicated cases to tertiary facilities) components towards reducing malaria morbidity and mortality [7].

A baseline survey was done during the inception phase of the programme to estimate the parasitological prevalence of malaria infection and record benchmark information on the awareness and knowledge of the community regarding the transmission, prevention and treatment of malaria and relevant health-seeking behaviour. The data generated is expected to fill in the knowledge gaps in social science aspects of malaria in Bangladesh and help programme develop informed intervention components and strategies (by BRAC and other NGOs), and also, future programme evaluation and impact assessment [10].

Methods

Data for this paper originated from the baseline survey conducted during July to November 2007, to cover the peak malaria season in Bangladesh. The 13 malaria-endemic districts were divided into two groups based on endemicity [11]: the five high endemic (parasitic prevalence 7.2%) south-eastern districts (henceforth SE area), and the eight low endemic (parasitic prevalence 0.5%) north-eastern districts (henceforth NE area) (Figure 1). The districts are composed of upazilas (sub-districts) divided into Unions, the latter again divided into mauzas (lowest administrative unit equivalent to, but not necessarily equal to, villages).
Figure 1

Two Malaria endemic areas of Bangladesh.

Sampling

Two-stage cluster sampling technique was employed to select the study sample. City Corporations and towns were excluded from this survey. For each of the 13 districts, all mauzas were listed and 30 mauzas were selected using a probability proportional to size (PPS) sampling procedure [11]. These mauzas were the primary sampling unit. Twenty-five households were selected using systematic random sampling from each mauza. Sample size was calculated using web-based software (C-Survey 2.0) based on the conservative estimates of malaria prevalence of 2%, design effect of 2, and precision of 1.5% at 95% confidence interval. This yielded a sample size of 750 individuals in each district for the study (total = 9,750).

The survey

The survey consisted of two parts: parasitological prevalence estimation by RDT and socioeconomic survey related to malarial knowledge and relevant health-seeking behaviour. For the latter, a semi-structured questionnaire was developed and pre-tested for ascertaining consistency, appropriateness of language, and sequencing before finalization [see Additional file 1]. The survey team comprised of experienced social science graduates who received rigorous training for five days on questionnaire content, probing techniques and strategies to establish rapport and neutrality essential to complete and accurate data collection. In hilly areas interviewers from ethnic groups were recruited to interview respective ethnic group of people.

In each mauza/village, the survey team selected every third household encountered as they moved from the center or periphery of the mauza/village following a designated path using the "spin the bottle" methodology [12]. When there were no respondents present in the selected households or the respondents refused to participate, the teams substituted it with an adjacent house. Beside estimating parasitological prevalence by RDT (Rapid Diagnostic Tests, 'FalciVax' by Zephyr Biomedicals, India) from one randomly chosen member (age>1 year) of each household, the survey questionnaire was administered in a face-to-face interview to the participant if adult or the household head (or spouse or any knowledgeable member of the household) if children to elicit information. Information was also collected for any febrile illness in the past 15 days among the household members and relevant health-seeking behaviour. Patients diagnosed as having malaria at the time of survey were referred for treatment as per national guideline.

The day-to-day field activities of the teams were fine-tuned by field researchers based in local offices and supervised by the principal author. Whenever necessary, re-interview was done by the supervisors for securing reliable and valid data. To improve the latter, an independent quality control team spot-checked households randomly within three days of the main survey. In cases where inconsistencies were noted, interviewers were accompanied by field supervisors until quality standards were met.

The variables

When individuals living together took meal from a common cooking facility, the entity is defined as a Household (HH). The head of Household is defined as the person who was perceived by household members to be the primary decision-maker in the family and who may or may not have been the main income-earner. Education was measured by completed years of formal schooling. Engagement in a particular income-earning activity for the major part of the day was categorized as 'main occupation'.

Wealth index was constructed following the method developed by Filmer and Pritchett [13]. The assets included for developing the index were: table, bed-cot, quilt, watch, radio, television, bi-cycle and electricity. Each of the variables was recorded into categorical dichotomous (yes, no) variable. Eight dichotomous variables were created and standardized. The principal component analysis was run with all constructed variables with certain criteria. The component score coefficient matrix was multiplied by the standardized variables to produce factor scores which were termed as household wealth score. The wealth scores were further classified into five quintiles, starting from the lowest (1st quintile, poorest) to highest (5th quintile, least poor).

Ethical considerations

The study received approval by the research review board and the ethical review board of ICDDR, B. Informed consent was obtained from the participants or their guardians before proceeding with the survey activities. Anonymity of the respondents at all stages of data analysis.

Results

Overall malaria prevalence rate in the 13 endemic districts was found to be 3.1% (Plasmodium falciparum 2.73%, Plasmodium vivax 0.16% and mixed infection 0.19%) by the Rapid Diagnostic Test 'FalciVax' (Zephyr Biomedicals, India) and is reported in detail elsewhere [11]. The prevalence was higher in the five south-eastern districts (7.2% as opposed to 0.5% in the north-eastern districts), with highest concentration in the three hill districts (11%).

The socio demographic and household characteristics of the study population are presented in Table 1 by the two study areas. Majority of the respondents (45%) were in their middle age (40–59 years). A greater proportion of respondents from NE districts (55%) compared to SE districts (45%) did not have any formal schooling, with a sex divide disfavouring the females. For males, involvement in farm activities was the most frequent occupation (about 41%), while this was household chores in case of females (around 65%). Less than 7% of the respondents were from female-headed households. Findings revealed that the households from SE area fared better than the other area when stratified in terms of asset quintiles e.g., the proportion of poorest households was 24% in the SE area compared to 18% in the NE area.
Table 1

Socio-demographic and household characteristics of the respondents study areas and sex (%)

 

South-eastern districts

North-eastern districts

 

M

F

All

M

F

All

Sociodemographic characteristics

Age (yrs)

      

   ≤19

0.1

0.8

0.2

0.5

0.2

0.5

   20–39

38.9

25.4

38.0

35.5

24.8

34.8

   40–59

43.7

53.2

44.4

45.3

54.9

45.9

   ≥60

17.2

20.6

17.5

18.8

20.1

18.9

Completed years of schooling

   None

42.8

69.4

44.6

53.6

75.2

55.1

   1–5

25.7

17.9

25.2

24.9

17.6

24.4

   >5

31.6

12.7

30.3

21.5

7.1

20.6

Main occupation

   Self-employment (agri.)

45.8

11.1

43.4

42.7

2.9

40.0

   Self-employment (non-agri)

23.0

3.2

21.6

21.9

2.9

20.6

   Wage-labour

10.2

9.9

10.2

17.0

8.8

16.5

   Service

10.6

4.8

10.2

7.4

2.9

7.1

   Domestic chores

0.7

61.5

4.8

1.1

69.9

5.8

   Others*

9.7

9.5

9.7

9.8

12.5

10.0

Household head

   Male

---

---

93.3

---

---

93.2

   Female

---

---

6.7

---

---

6.8

Household asset quintiles

   Poorest

---

---

23.6

---

---

18.0

   2nd

---

---

21.3

---

---

21.6

   3rd

---

---

18.1

---

---

18.5

   4th

---

---

19.7

---

---

20.3

   Least poor

---

---

17.4

---

---

21.6

N

3498

252

3750

5548

408

5999

*beggar, unemployed, too old/sick to work etc.

Tables 2, 3 and 4 present malarial awareness of the respondents with respect to sex, educational attainment and household economic status (as proxied by asset quintiles) respectively. In general, the respondents were aware about the cause ('mosquito bite') and presenting symptoms of malarial illness ('fever with shivering') irrespective of sex, and this awareness increased uniformly with years of schooling as well as level of affluence (p < 0.001). However, when they were asked about its mode of transmission, only around 39% in the SE area and 32% in the NE area could respond correctly ('by bite of mosquito which has bitten a malarial patient') (p < 0.001, Table 2), and was also found to be a factor of schooling years and affluence (p < 0.001, Tables 3 and 4 respectively).
Table 2

Reported knowledge on malaria by study areas and sex (multiple responses)

 

South-eastern districts

North-eastern districts

χ2 significance

 

M

F

All

M

F

All

 
 

a

b

c

d

e

f

c vs f

Causes of malaria

       

   Mosquito bite

90.7

89.2

90.6

94.4

91.9

94.2

p < 0.001

   Fly/insect bite

4.8

4.0

4.7

2.0

1.7

2.0

p < 0.001

   Not maintaining neat and cleanliness

10.5

7.6

10.3

16.0

5.2

15.9

p < 0.001

   Others

3.5

4.2

5.4

3.5

4.2

3.6

p < 0.001

Symptoms of malaria

       

   Onset of fever with shivering

76.4

72.1

76.1

83.2

81.1

83.0

p < 0.001

   Fever at intervals

19.8

22.3

21.0

25.6

27.7

25.8

p < 0.001

   Remission of fever with sweating

10.5

7.6

10.3

16.0

15.2

15.9

p < 0.001

   Others

18.5

18.7

18.5

10.3

8.6

10.2

p < 0.001

Mode of transmission

       

   By bite of any mosquito

33.4

36.3

33.5

32.9

36.0

33.1

ns

   By bite of mosquito which has bitten a malarial patient

39.2

29.9

38.6

32.5

31.9

32.4

p < 0.001

   Don't know

24.4

28.3

24.7

30.6

27.7

30.4

p < 0.001

   Other

3.1

3.6

3.1

6.9

7.4

6.9

p < 0.001

Mode of prevention

       

   Preventing breeding of mossquito

13.3

6.8

12.9

17.6

18.6

17.7

p < 0.001

   Using bednet

84.1

83.3

84.0

84.3

80.9

84.1

ns

   Using insecticide impregnated bednet

1.0

0.8

1.0

2.1

2.7

2.1

p < 0.001

   Using mosquito repellent/coil

16.1

13.1

15.9

19.9

20.8

20.0

p < 0.001

   Other

12.3

15.1

12.5

9.4

10.5

9.5

p < 0.001

Mode of treatment

       

   Allopathic treatment

96.0

96.0

96.0

98.3

97.3

98.2

p < 0.001

   Traditional (Herbal/Kabiraji)

1.7

1.2

1.7

1.1

2.0

1.1

p < 0.01

   Faith healing

0.5

0.0

0.3

0.3

0.2

0.3

ns

   Homeopathic

0.5

0.0

0.3

0.3

0.2

0.3

ns

   Other

0.8

1.2

0.8

0.2

0.5

0.2

p < 0.001

Source of information

       

   Govt. health worker

21.2

23.5

20.7

25.1

23.5

25.0

p < 0.001

   NGO health worker

26.8

18.7

26.3

16.7

14.2

16.5

p < 0.001

   Radio/TV/Newspaper

14.5

15.5

14.6

15.2

13.0

15.0

ns

   Poster/leaflet

2.4

5.6

2.6

12.9

3.2

2.0

p < 0.05

   Neighbours/relatives

34.8

43.8

35.4

48.2

27.1

48.8

p < 0.001

   Self

16.9

13.9

15.8

14.7

9.6

11.4

p < 0.05

   Other

5.7

6.0

5.7

4.2

4.2

4.2

p < 0.001

N

3499

251

3750

5591

408

5999

 
Table 3

Reported knowledge on malaria by study areas and completed years of schooling (multiple responses)

 

South-eastern districts

North-eastern districts

 

Completed years of schooling

 

None

1–5

>5

χ2 significance

None

1–5

>5

χ2 significance

Causes of malaria

        

   Mosquito bite

87.4

91.6

94.7

p < 0.001

93.0

95.0

96.6

p < 0.001

   Fly/insect bite

4.5

4.5

5.2

ns

1.6

1.9

3.1

p < 0.01

   Not maintaining neat and cleanliness

8.3

11.6

12.1

p < 0.001

15.0

13.6

21.2

p < 0.001

   Others

7.1

4.5

3.7

p < 0.001

4.4

3.0

1.9

p < 0.001

Symptoms of malaria

        

   Onset of fever with shivering

71.9

77.2

81.6

p < 0.001

80.0

84.9

88.8

p < 0.001

   Fever at intervals

19.2

18.4

22.5

p < 0.05

26.8

22.7

26.7

p < 0.05

   Remission of fever with sweating

8.8

11.6

12.1

p < 0.001

15.0

13.6

21.2

p < 0.001

   Others

18.5

17.6

19.2

ns

10.9

9.4

9.2

ns

Mode of transmission

        

   By bite of any mosquito

34.9

37.2

28.4

p < 0.001

33.2

35.7

30.0

p < 0.05

   By bite of mosquito which has bitten a malarial patient

29.2

38.9

52.2

p < 0.001

27.5

28.5

49.8

p < 0.001

   Don't know

29.2

21.2

20.8

p < 0.001

33.6

31.9

20.2

p < 0.001

   Other

3.2

3.1

3.0

ns

7.7

6.3

5.6

p < 0.05

Mode of prevention

        

   Preventing breeding of mosquito

7.8

12.9

20.3

p < 0.001

16.8

14.0

24.4

p < 0.001

   Using bed net

80.9

84.4

88.4

p < 0.001

81.4

85.2

89.7

p < 0.001

   Using insecticidal bed net

0.8

1.1

1.3

ns

1.6

2.6

2.9

p < 0.01

   Using mosquito repellent/coil

11.2

17.1

22.1

p < 0.001

15.6

21.6

30.0

p < 0.001

   Other

14.2

12.4

10.2

p < 0.05

10.9

9.0

6.5

p < 0.001

Mode of treatment

        

   Allopathic treatment

94.3

96.2

98.3

p < 0.001

97.8

98.3

99.0

p < 0.02

   Traditional (Herbal/Kabiraji)

2.0

1.4

1.4

ns

1.0

1.4

1.1

ns

   Faith healing

0.5

0.5

0.5

ns

0.2

0.3

0.3

ns

   Homeopathic

0.5

0.4

0.3

ns

0.2

0.3

0.6

ns

   Other

1.2

0.7

0.4

p < 0.05

0.3

0.1

0.0

ns

Source of information

        

   Govt. health worker

17.8

19.9

25.5

p < 0.001

22.7

23.5

32.9

p < 0.001

   NGO health worker

23.6

25.9

30.6

p < 0.001

15.0

17.0

20.5

p < 0.001

   Radio/TV/Newspaper

9.4

16.5

20.7

p < 0.001

12.0

13.4

24.8

p < 0.001

   Poster/leaflet

1.5

2.8

4.2

p < 0.001

2.0

1.1

2.9

p < 0.01

   Neighbours/relatives

41.6

35.7

25.8

p < 0.001

54.7

48.5

33.2

p < 0.001

   Self

13.3

16.6

19.5

p < 0.001

12.0

16.5

18.0

p < 0.001

   Other

6.5

6.5

4.0

p < 0.01

4.5

4.5

3.3

ns

N

1683

938

1129

 

3322

1453

1224

 
Table 4

Reported knowledge on malaria by study areas and wealth quintiles (multiple responses)

 

South-eastern districts

North-eastern districts

 

Household asset quintiles

 

Poorest

3rd Quin.

Least poor

χ2 significance

Poorest

3rd Quin.

Least poor

χ2 significance

Causes of malaria

        

   Mosquito bite

84.8

90.7

95.5

p < 0.001

92.2

93.2

96.7

p < 0.001

   Fly/insect bite

4.6

5.0

6.5

ns

0.8

1.6

4.4

p < 0.001

   Not maintaining neat and cleanliness

7.9

10.6

13.4

p < 0.01

10.1

16.6

22.6

p < 0.001

   Others

8.0

5.3

3.4

p < 0.001

5.0

4.3

1.6

p < 0.001

Symptoms of malaria

        

   Onset of fever with shivering

68.7

76.8

82.9

p < 0.001

76.3

85.0

86.5

p < 0.001

   Fever at intervals

17.6

20.6

21.0

ns

25.7

21.7

32.1

p < 0.05

   Remission of fever with sweating

7.9

10.6

13.4

p < 0.01

10.1

16.6

22.6

p < 0.001

   Others

21.9

17.8

16.1

p < 0.01

12.7

9.0

9.8

p < 0.001

Mode of transmission

        

   By bite of any mosquito

30.8

33.4

39.3

p < 0.05

29.9

30.1

38.6

p < 0.001

   By bite of mosquito which has bitten a malarial patient

30.5

40.1

43.0

p < 0.001

23.7

30.9

43.7

p < 0.001

   Don't know

31.0

32.9

18.6

p < 0.001

39.5

32.0

19.3

p < 0.001

   Other

1.9

4.0

3.7

p < 0.05

6.4

9.7

4.9

p < 0.001

Mode of prevention

        

   Preventing breeding of mosquito

6.8

13.1

17.8

P < 0.001

8.9

17.9

26.4

p < 0.001

   Using bed net

70.1

84.4

89.4

P < 0.001

84.6

80.4

87.1

p < 0.001

   Using insecticidal bed net

0.7

1.5

1.2

ns

0.9

2.7

2.3

p < 0.05

   Using mosquito repellent/coil

8.0

15.6

24.6

P < 0.001

13.2

16.4

32.6

p < 0.001

   Other

16.9

12.5

8.8

p < 0.001

10.1

11.9

7.0

p < 0.001

Mode of treatment

        

   Allopathic treatment

92.6

95.7

98.6

p < 0.001

97.2

98.5

98.6

p < 0.05

   Traditional (Herbal/Kabiraji)

2.4

1.6

1.7

ns

1.2

1.0

1.2

ns

   Faith healing

0.2

0.6

0.6

ns

0.2

0.2

0.4

ns

   Homeopathic

0.2

0.1

0.5

ns

0.1

0.2

0.5

ns

   Other

1.5

0.6

0.0

p < 0.05

0.6

0.0

0.0

p < 0.001

Source of information

        

   Govt. health worker

17.8

21.6

22.1

ns

28.1

22.3

26.2

p < 0.05

   NGO health worker

23.9

29.7

19.5

p < 0.001

14.3

17.5

16.7

ns

   Radio/TV/Newspaper

5.3

13.5

32.4

p < 0.001

4.1

10.5

31.6

p < 0.001

   Poster/leaflet

0.9

1.8

6.9

p < 0.001

0.3

2.1

2.7

p < 0.001

   Neighbours/relatives

43.9

35.0

28.1

p < 0.001

50.6

53.7

37.9

p < 0.001

   Self

12.4

15.0

21.4

p < 0.001

13.3

13.8

18.3

p < 0.001

   Other

5.2

6.8

5.4

ns

6.5

3.8

3.6

p < 0.001

N

884

680

651

 

1082

1108

1294

 

Interestingly, the use of bed net for prevention of malaria was singled out uniformly by the respondents (>80%,) (Table 2). Other measures reported were: preventing breeding of mosquito (13% in SE area and 18% in NE area, p < 0.001), using mosquito repellant/coil (16% in SE area and 20% in NE area, p < 0.001). Though there was not much variation by sex (Table 2), but the trend observed earlier with education and affluence remained valid with one exception (Tables 3 and 4 respectively). The respondents almost unanimously reported allopathic medicine to be the treatment for malaria (>98%), especially the more educated and the affluent ones (Tables 3, 4 respectively).

Neighbours and relatives were the most frequently mentioned group for malaria-related information (35% in SE and 49% in NE areas respectively, p < 0.001) by the respondents, especially the females (Table 2). However, with increasing level of education and affluence (p < 0.001, Tables 3 and 4 respectively), the proportion decreased gradually to be replaced by community health workers from government and NGOs. Mass media (Radio/TV/Newspaper) and printing media (poster/leaflet) became increasingly important means of message dissemination in those instances.

Around 2% of the respondents in SE area and 0.4% respondents in NE area reported to have had suffered from fever with shivering within 15 days prior to the day of survey (p < 0.001). No sex difference in fever prevalence was seen (Table 5). Next, information on their health-seeking behaviour was elicited. Majority of these patients did not seek any treatment, women more so than men and those from SE area more so than those in the NE area. Self-treatment was practiced more frequently by patients from NE area (14%) than by those from SE area (11%). Professional allopathic practitioners were consulted in 13% of instances in both areas, with a gender gradient disfavoring women. On the other hand, drugstore salespeople were consulted more frequently by those from the SE area (47%) compared to the NE area (32%), with marginal or no gender difference (Table 5). When disaggregated by education and SES, a decrease in proportion of no-treatment and a simultaneous increase in treatment seeking from professional allopaths i.e., MBBS doctors was observed with increasing level of education and affluence (Table 6).
Table 5

Prevalence of fever with shivering in past 15 days prior to the day of survey and relevant health-seeking behaviour %

 

South-eastern districts

North-eastern districts

χ2 significance

 

M

F

All

M

F

All

 
 

a

b

c

d

e

f

C vs f

Had fever with shivering in last 15 days

1.7

2.0

1.8

0.5

0.4

0.4

p < 0.001

N

10147

9675

19822

16025

14962

30987

 

Health-seeking behaviour

       

   No treatment

35.8

41.3

38.7

20.5

25.4

22.7

 

   Self-treatment

10.4

11.1

10.8

15.1

11.9

13.6

 

   Drug store salespeople

35.3

29.6

32.3

45.2

49.2

47.0

 

   Paraprofessionals

2.3

4.8

3.6

2.7

3.4

3.0

 

   Professional allopaths (MBBS doctors)

14.5

11.6

13.0

16.4

8.5

12.9

 

   Others

1.7

1.6

1.7

0.0

1.7

0.8

 

χ2 significance

ns

  

ns

   

N

173

189

362

73

59

132

 
Table 6

Health-seeking behaviour of patients by education and affluence %

 

South-eastern districts

North-eastern districts

 

Years of schooling

 

None

1–5

>5

None

1–5

>5

No treatment

39.1

41.1

28.8

20.7

26.3

10.0

Self-treatment

12.8

7.5

15.3

10.3

13.2

25.0

Drug store salespeople

33.8

31.8

32.2

55.2

39.5

35.0

Paraprofessionals

4.5

1.9

5.1

0.0

5.3

10.0

Professional allopaths (MBBS doctors)

9.0

15.9

16.9

12.1

15.8

20.0

Others

0.8

1.9

1.7

1.7

0.0

0.0

χ2 significance

ns

  

ns

  

N

133

107

59

58

38

20

 

Household asset quintiles

 

South-eastern districts

North-eastern districts

 

Poorest

3rd Quin.

Least poor

Poorest

3rd Quin.

Least poor

No treatment

47.2

30.6

27.6

29.2

28.6

16.0

Self-treatment

10.4

14.5

10.3

16.7

14.3

24.0

Drug store salespeople

26.4

30.6

37.9

37.5

52.4

36.0

Paraprofessionals

3.2

6.5

3.4

0.0

0.0

0.0

Professional allopaths (MBBS doctors)

11.2

12.9

17.2

12.5

4.8

24.0

Others

1.6

4.8

3.4

4.2

0.0

0.0

χ2 significance

ns

  

ns

  

N

125

62

29

24

21

25

Finally, Table 7 shows that there was delay in initiation of treatment beyond 24 hours in majority of the instances, and the illness also prolonged beyond seven days, especially in the NE area (p < 0.01). This resulted in the disruption of income-earning activities beyond five days, more so in the NE area (p < 0.01).
Table 7

Time to treatment initiation, duration, disruption of income-earning and illness expenditure by study areas and sex

 

South-eastern districts

North-eastern districts

significance

 

M

F

All

M

F

All

 
 

a

b

c

d

e

f

c vs. f

Treatment initiated %

      

p < 0.01

   Within 24 hours

44.8

41.7

43.2

24.6

27.3

25.7

2)

   Beyond 24 hours

55.2

58.3

56.8

75.4

72.7

74.3

 

Duration of illness %

      

p < 0.01

   ≤ 3 days

29.1

33.9

31.7

19.6

21.9

20.5

2)

   4–7 days

50.5

36.4

43.0

28.3

37.5

32.1

 

   ≥ 7 days

20.4

29.7

25.3

52.2

40.6

47.4

 

Days income-earning was disrupted (mean)

5.0

5.3

5.1

7.0

9.2

7.6

p < 0.003

(t-test)

*beggar, unemployed, too old/sick to work etc.

Discussion

The role of social science research in the design and implementation of evidence-based prevention, management and control strategies for malaria cannot be overemphasized [14]. There is lack of this kind of data in Bangladesh and this baseline survey on malaria has attempted to fill in this knowledge gap besides estimation of parasitological prevalence from a population based survey in the 13 endemic districts. Findings revealed superficial knowledge on malarial transmission, prevention and treatment, especially among the poor and the illiterate. A gender and geographical divide with respect to different aspects of malaria prevention and treatment was observed, disfavouring women and south-eastern area respectively. While the respondents preferred allopathic providers for treatment of malaria unanimously, a 'know-do' gap in practices existed. In about half of the instances, a delay in seeking care for malaria-like fever was observed. These are discussed below with its implications for programme implementation

The awareness of the respondents that malaria is caused and transmitted by bite of mosquito is usually a common knowledge in malaria endemic countries such as India, Turkey, Nepal, Haiti, Latin America, Sudan and Ghana [1522]. However, only a tiny fraction of the respondents could accurately state the correct transmission route ('by bite of mosquito which has bitten a malarial patient') and none could state how the mosquito becomes infective i.e., the parasitological cause. The serious gaps in knowledge are also revealed by one-third of the respondents stating that they did not knew the mode of transmission and another one-third stating that any mosquito bite causes malaria. The poor and the semi-literate are especially disadvantaged in these aspects. Health education interventions should be designed according to the existing knowledge and awareness level of vulnerable population as well as their current treatment-seeking practices, and should be implemented for sufficient length of time to be effective [20].

The association of febrile illness with malaria has been known in Bangladesh for a long time [23]. This is also reiterated in this study, where the majority of the respondents mentioned fever (with shivering, at intervals) as the most common symptom of malaria and is consistent with observations from other countries [16, 18, 20, 21, 2426].

Knowledge on the use of bed net as a preventive measure against mosquito bite was high among the respondents in this study. Similar high level of knowledge on preventive use of bed net had been observed in Nepal [18] and Ghana [22], but not in countries such as Ethiopia [25], Iran [26], Delhi, India [16], Turkey [17], and Haiti [19]. This advantage will make the work of the programme easier in introducing insecticidal bed nets (LLINs/ITNs) as a strategic measure for preventing malaria transmission. However, the programme also needs to keep the equity perspective in focus, while distributing insecticidal bed nets, because the poorer households were found to be disadvantaged in this respect.

The respondents were unanimous about seeking treatment from the allopathic providers, whether in the formal or informal sector. However, the 'know-do' gap became especially evident when in practice majority of the ill persons either did not seek any treatment or practiced self-treatment. The latter is consistent with findings from Turkey, where the majority practice self-treatment for malaria [17]. Of those who sought treatment, the majority went to the informal allopathic providers, such as village doctors and drugstore salespeople whose knowledge and capacity for curative treatment is not without question [27]. Also, there was a delay in the beginning of treatment in more than half of the instances of febrile episodes suggestive of malaria, and there was disruption of income-earning activities due to prolonging of the illness. Thus, efforts will be needed to educate this population on the need for 'Early Diagnosis and Prompt Treatment (EDPT)' for reducing its income-erosion effect. Further, the capacity of the informal allopathic providers (important for treatment of poor) should be developed in the use of Rapid Diagnostic Tests (RDTs), and the rational use of artemisinin-based combination drugs (such as Coartem®) so as to fast-track informed diagnosis and treatment.

Throughout this study gender divide in knowledge, awareness and health-seeking behaviour was observed disfavouring women. This is not surprising, given the patriarchal norms in the society and was also noted earlier in other studies [28]. While designing interventions, pro-active measures should be undertaken by malarial prevention and control programmes to reduce this gender gap. This is all the more necessary because experiences show that even women-focused interventions may not increase access of quality health care for women, if the gender issues are not explicitly addressed by the programme [29].

Lastly, there are regional differences. The SE area was found to have greater proportion of poorest households (in terms of asset quintiles) than the NE area. The SE area respondents also appeared to be disadvantaged regarding different aspects of malaria prevention and treatment than the NE area, though marginally. However, this difference has to be taken into consideration while allocating resources for specific interventions.

Conclusion

The findings of the survey have important implications for fine-tuning the current malaria prevention and control programme. The programme should disseminate comprehensive information on different aspects of malaria for converting the 'unfelt' need to 'felt' need of the community to facilitate the uptake of preventive and curative measures. This is all the more necessary as it has been found elsewhere that knowledge of malaria influences the use of preventive measures such as use of insecticidal nets (30). Intensive campaign for practicing EDPT is necessary so that the community is convinced about its need for reducing malaria mortality, especially among the vulnerable groups. Besides print and electronic media, various informal communication methods (e.g., folk songs, people's theatre etc.) can be used to reach the disadvantaged sections of this largely illiterate community. Finally, equity focus in terms of gender, SES and geographical location should be maintained at every stage of programme implementation.

Declarations

Acknowledgements

We would like to express our heartiest gratitude to the Global Fund for AIDS, Tuberculosis and Malaria (GFATM) for giving us the opportunity to be part of the programme in Bangladesh through research. We specially thank the programme for giving all out cooperation, especially to the Malaria Prevention and Control Programme of BRAC without whose support and assistance it would not have been possible to conduct this survey. We take this opportunity to thank researchers from BRAC and ICDDR, B, for their participation and contribution in the design and implementation of the study.

Authors’ Affiliations

(1)
BRAC Research and Evaluation Division, BRAC Centre
(2)
ICDDR

References

  1. Greenwood BM, Bojang K, Whitty CJM, Targett GA: Malaria. Lancet. 2005, 365: 1487-1498. 10.1016/S0140-6736(05)66420-3.View ArticlePubMedGoogle Scholar
  2. Barat LM, Palmer N, Basu S, Worrall E, Hanson K, Mills A: Do malaria control interventions reach the poor? A view through the equity lens. Am J Trop Med Hyg. 2004, 71 (Suppl 2): 174-178.PubMedGoogle Scholar
  3. Worrall E, Basu S, Hanson K: Is malaria a disease of poverty? A review of literature. Trop Med Int Health. 2005, 10: 1047-1059. 10.1111/j.1365-3156.2005.01476.x.View ArticlePubMedGoogle Scholar
  4. Howard N, Chandromohan D, Freeman T, Shafi A, Rafi M, Enaetullah S, Rowland M: Socioeconomic factors associated with the purchasing of insecticide treated nets in Afghanistan and their implications for social marketing. Trop Med Int Health. 2003, 8: 1043-1050. 10.1046/j.1365-3156.2003.01163.x.View ArticlePubMedGoogle Scholar
  5. Mutabingwa TK: Artemisinin-based combination therapies (ACTs): Best hope for malaria treatment but inaccessible to the needy!. Acta Trop. 2005, 95: 305-315. 10.1016/j.actatropica.2005.06.009.View ArticlePubMedGoogle Scholar
  6. Rusell S: The economic burden of illness for households in developing countries: A review of studies focusing on malaria, tuberculosis and Human Immunodeficiency virus/acquired immunodeficiency syndrome. Am J Trop Med Hyg. 2004, 71 (Suppl 2): 147-155.Google Scholar
  7. BHP (BRAC Health Programme): Annual Report 2007. Dhaka. 2007Google Scholar
  8. Bangladesh Malaria Proposal to GFATM (Annex to Program Grant Agreement). [http://www.theglobalfund.org/programs/grant/?lang=en%26compid=1267%26granid=532%26countryid=BAN]
  9. BRAC: BRAC Annual Report 2007. Dhaka. 2008Google Scholar
  10. Breman JG, Alilio MS, Mills A: Conquering the intolerable burden of malaria: what's new, what's needed: A summary. Am J Trop Med Hyg. 2004, 71 (Suppl 2): 1-15.PubMedGoogle Scholar
  11. Ahmed SM, Islam MA, Haque R, Hossain M: Malaria Baseline Prevalence and Socioeconomic Survey 2007. 2008, Dhaka: BRAC Research and Evaluation Division, ICDDR, B & Government of BangladeshGoogle Scholar
  12. Sintasath DM, Ghebremeskel T, Lynch M, Kleinau E, Bretas G, Shililu J, Brantly E, Graves PM, Beier J: Malaria prevalence and associated risk factors in Eritrea. Am J Trop Med Hyg. 2005, 71: 682-687.Google Scholar
  13. Filmer D, Pritchett L: Estimating wealth effects without expenditure data-tears: An application to educational enrollments in states of India. World Bank Policy Research Working Paper No. 1994. 2000, Washington DC: World BankGoogle Scholar
  14. Mwensi HA: Social science research in malaria prevention, management and control in last two decades: An overview. Acta Trop. 2005, 95: 292-297. 10.1016/j.actatropica.2005.06.004.View ArticleGoogle Scholar
  15. Sharma AK, Bhasin S, Chaturvedi S: Predictors of knowledge about malaria in India. J Vector Borne Diseases. 2007, 44: 189-197.Google Scholar
  16. Tyagi P, Roy A, Malhotra MS: Knowledge, awareness and practices towards malaria in communities of rural, semi-rural and bordering areas of east Delhi (India). J Vector Borne Diseases. 2005, 42: 30-35.Google Scholar
  17. Simsek Z, Kurcer MA: Malaria: knowledge and behaviour in an endemic rural area of Turkey. Public Health. 2005, 119: 202-208. 10.1016/j.puhe.2004.03.011.View ArticlePubMedGoogle Scholar
  18. Joshi AB, Banjara MR: Malaria related knowledge, practices and behaviour of people in Nepal. J Vector Borne Diseases. 2008, 45: 44-50.Google Scholar
  19. Keating J, Eisele TP, BeNEt A, Johnson D, Mcintyre K: A description of malaria-related knowledge, perceptions, and practices in the Artibonite Valley of Haiti: Implications for malaria control. Am J Trop Med Hyg. 2008, 78: 262-269.PubMedGoogle Scholar
  20. Kroeger A, Meyer R, Mancheno M, Gonzalez M: Health education for community-based malaria control: an intervention study in Ecuador, Columbia and Nicaragua. Trop Med Int Health. 1996, 1: 836-846.View ArticlePubMedGoogle Scholar
  21. Adam I, Omer EM, Salih A, Khamis AH, Malik EM: Perceptions of the causes of malaria and of its complications, treatment and prevention among midwives and pregnant women of Eastern Sudan. J Public Health. 2008, 16: 129-132. 10.1007/s10389-007-0124-2.View ArticleGoogle Scholar
  22. De La Cruz N, Crookston B, Dearden K, Gray B, Ivins N, Alder S, Davis R: Who sleeps under bednets in Ghana: A doer/non-doer analysis of malaria prevention behaviours. Malar J. 2006, 5: 61-10.1186/1475-2875-5-61.PubMed CentralView ArticlePubMedGoogle Scholar
  23. Faiz MA: A study on clinical presentation of malaria. Bangladesh Medical J. 1982, 11: 41-52.Google Scholar
  24. Das ML, Paudel IS, Nirauta SR, Roy L: Knowledge, attitude and practice about malaria and mosquito nets in two villages of Nepal. Indian J Practicing Doctor. 2007, 4 (1): [http://www.indmedica.com/journals.php?journalid=3%26issueid=94%26articleid=1278%26action=article]Google Scholar
  25. Jima D, Tesfaye G, Deresssa W, Woyessa A, Kebedi D, Alamirew D: Baseline survey for the implementation of insecticide treated mosquito nets in malaria control in Ethiopia. Ethiopian J health Dev. 2005, 19: 16-23.View ArticleGoogle Scholar
  26. Rakhshani F, Moghadam ARA, Alemi R, Moradi A: Knowledge, perceptions and prevention of malaria among women in Sistan va Baluchestan, Islamic Republic Iran. Eastern Mediterranean Health J. 2003, 9: 248-256.Google Scholar
  27. Ahmed SM, Hossain MA: Knowledge and practice of unqualified and semi-qualified allopathic providers in rural Bangladesh: implications for the HRH problem. Health Policy. 2007, 84: 332-343. 10.1016/j.healthpol.2007.05.011.View ArticlePubMedGoogle Scholar
  28. Ahmed SM: Exploring health-seeking behaviour of disadvantaged populations in rural Bangladesh. PhD thesis. 2005, Stockholm, Sweden: Karolinska University Press, [http://diss.kib.ki.se/2005/91-7140-435-X/]Google Scholar
  29. Ahmed SM, Petzold M, Kabir ZN, Tomson G: Targeted intervention for the ultra poor in rural Bangladesh: does it make any difference in their health-seeking behaviour?. Soc Sci Med. 2006, 63: 2899-2911. 10.1016/j.socscimed.2006.07.024.View ArticlePubMedGoogle Scholar
  30. Nganda RY, Drakeley D, Reyburn H, Marchant T: Knowledge of malaria influences the use of insecticide treated nets but not intermittent presumptive treatment by pregnant women in Tanzania. MalarJ. 2004, 3: 42-10.1186/1475-2875-3-42.View ArticleGoogle Scholar

Copyright

© Ahmed et al; licensee BioMed Central Ltd. 2009

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Advertisement