Household knowledge, perceptions and practices of mosquito larval source management for malaria prevention and control in Mwanza district, Malawi: a cross‐sectional study
Mosquito larval source management (LSM) is a key outdoor malaria vector control strategy in rural communities in sub-Saharan Africa. Knowledge of this strategy is important for optimal design and implementation of effective malaria control interventions in this region. This study assessed household knowledge, perceptions and practices of mosquito LSM methods (draining stagnant water, larviciding, clearing grass/bushes and clean environment).
Methods
A cross-sectional design was used whereby 479 households were selected using two-stage sampling in Mwanza district, Malawi. A household questionnaire was administered to an adult member of the house. Respondents were asked questions on knowledge, perceptions and practices of mosquito LSM methods. Multivariable logistic regression model was used to identify factors associated with high-level knowledge of mosquito LSM methods.
Results
Majority of the respondents (64.5%) had high-level knowledge of mosquito LSM methods. Specifically, 63.7% (200/314) had positive perceptions about draining stagnant water, whereas 95.3% (223/234) practiced clean environment for malaria control and 5.2% had knowledge about larviciding. Compared to respondents with primary education, those with secondary education were more likely, whereas those without education were less likely, to have high-level knowledge of mosquito LSM methods (AOR = 3.54, 95% CI 1.45–8.63 and AOR = 0.38, 95% CI 0.23–0.64, respectively). Compared to respondents engaged in crop farming, those engaged in mixed farming (including pastoralists) and the self-employed (including business persons) were more likely to have high-level knowledge of mosquito LSM methods (AOR = 6.95, 95% CI 3.39–14.23 and AOR = 3.61, 95% CI 1.47–8.86, respectively). Respondents living in mud-walled households were less likely to have high-knowledge of mosquito LSM methods than those living in brick-walled households (AOR = 0.50, 95% CI 0.30–0.86).
Conclusions
A high-level knowledge of mosquito LSM methods was established. However, when designing and implementing this strategy, specific attention should be paid to the uneducated, crop farmers and those living in poor households.
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Abkürzungen
AOR
Adjusted odds ratio
b
Cluster size
CI
Confidence interval
COR
Crude odds ratio
LSM
Larval source management
MPAC
Malaria Policy Advisory Committee
NHSRC
National Health Sciences Research Committee
roh
Rate of homogeneity
NIMR
National Institute for Medical Research
SI
Sampling interval
WHO
World Health Organization
Background
Malaria remains a global health challenge due to its high disease burden [1]. Sub-Saharan Africa (SSA) region has high temperatures and rainfall climate that present favourable breeding environment for malaria-transmitting anopheline mosquitoes [1] such that malaria is the leading cause of death and illness in SSA [2]. Over 15% of hospital admissions in this region are due to malaria [3]. Almost all Malawians are at risk of malaria [4]. Malaria is among diseases that lead to years-lost-to-disability (YLD); 30% of outpatient visits are due to malaria in Malawi [5]. Over 40% of hospital admissions are among children under 5 years old in Malawi [6]. Most malaria control interventions ignore the main culprit: outdoor transmission [7]. Thus, an effective policy setting is critical to fight malaria in the wake of financial constraints and increased resistance of Plasmodium falciparum to anti-malarial drugs [2]. The World Health Organization (WHO) established a Malaria Policy Advisory Committee (MPAC) to set evidence-informed policies for implementation to control and eliminate malaria in WHO member states [8], and MPAC attributed the worldwide achievements in malaria control over the past decade to major investments in vector control [9]. Malawi spends much financial resource on indoor transmission interventions [10] but outdoor mosquito biting remains a challenge in SSA countries, including Malawi [11]. Mosquito larval source management (LSM) methods would be useful to eliminate the main malaria vectors in SSA: Anopheles gambiae and Anopheles arabiensis [11]. Limited community participation, however, has been identified as the main barrier to LSM in Malawi [12]. Evidence suggests that the strategy is cheap and easily implementable at household and community levels [11]. This study assessed household knowledge, practices and perceptions of mosquito LSM methods to guide the design and implementation of effective malaria control interventions in rural Malawian communities.
Methods
Study design
A cross-sectional design was conducted in Nthache area in Mwanza district, Malawi (Fig. 1).
Fig. 1
Map of Traditional Authority Nthache in Mwanza district, Malawi
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Sampling
A sample size of 497 households was calculated using Cochran formula [13]. A non-response rate of 10% and a proportion of 30% with knowledge of mosquito LSM methods were assumed based on a similar rural Kenyan study [14]. A design effect of 1.4 was calculated based on a cluster size, b of 15 and a rate of homogeneity of 0.025 [15]. Level of precision was set at 0.05. Sample size was adjusted to 500 to maintain an equal number of 20 households per cluster. Some 479 respondents were interviewed as 21 respondents were unavailable. A two-stage cluster random sampling procedure was used to select households for this study.
In Stage 1, 25 clusters were randomly selected from 43 villages that form Nthache area, using probability proportional to population size. Each selected village formed a cluster or two clusters depending on population size (Additional file 1). Prior to random selection of clusters, a sampling interval (SI) was calculated after dividing the total population in the study area (33,870) into 25 clusters. Cumulative population sizes for the villages were calculated by size of the population for each village [13]. A range was developed for each village according to its cumulative population size. To determine clusters, a number 52 was randomly selected between 1 and a calculated SI of 1,354.8. The village with a range that contained the number 52 was identified as the first cluster. The SI was then added to 52 to determine the second cluster. This process continued as SI was added to the immediate calculated result until 25 clusters were identified [13].
In stage 2, village registers from the sampled clusters were used to assign households with identification numbers. Small pieces of paper with identification numbers were put in a pot, from which 20 households were selected per cluster.
Research variables
A validated household questionnaire was used to collect data. Respondents were asked questions on socio-demographic characteristics, knowledge, perceptions, and practices related to specific mosquito LSM methods. An adult member in the household was interviewed (> 18 years old). In child-headed households (< 18 years-old), the heads were interviewed. An adult member from the sampled household who had consented to respond to survey questionnaires was included.
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Gender of the respondent was classified and coded as female, 1 and male, 2. Data on age was collected as a continuous variable and categorized as well as coded into a binary variable of ≤ 35 years: 1, > 35 years: 2. Education status was classified and coded as primary: 1, secondary: 2, none: 3, informal/pre-primary: 4. Marital status was classified and coded as married: 1, single: 2, widowed: 3, divorced/separated: 4. Pregnancy status was classified and coded as being not-pregnant: 1, pregnant: 2. Occupation was classified and coded as crop farming: 1, mixed farming/pastoralist: 2, business/self-employed: 3, unemployed/student: 4, employed: 5, housewife: 6, other: 7. Household ownership was classified and coded as owned: 1, rented: 2. Household floor was categorized and coded as natural/earth: 1, cement/tiles: 2. Household roof was classified and coded as grass/thatch: 1, iron sheets: 2. Wall type was classified and coded as brick wall: 1, mud wall: 2. Energy used was classified and coded as firewood: 1, charcoal: 2.
Level of knowledge was measured as a binary variable (1-high-level and 0-low-level). A scoring system known as knowledge score was developed to assess the level of knowledge. To score full points (4 points), respondents had to mention four methods: draining stagnant water (1 point), larviciding (1 point), clearing grass/bushes (1 point), and clean environment (1 point). A mean score of 1.73 was calculated. Respondents with scores above the mean were deemed to have high knowledge whereas those below it were deemed to have low knowledge of mosquito LSM methods [16]. Respondents were asked to mention specific mosquito LSM methods. They could provide multiple responses from this list: draining stagnant water, larviciding, clearing grass/bushes, clean environment. Those who stated correct answers were deemed as having knowledge whereas those with incorrect/unstated answers as not having knowledge. The responses were coded as 1: having knowledge, 0: not having knowledge. Respondents were asked to mention one specific mosquito LSM method they perceived as the most effective for malaria control among those they initially expressed knowledge of. The responses were coded as 1: positive perceptions, 0: no positive perceptions. Respondents were asked to mention specific mosquito LSM methods they practice for malaria control they initially expressed knowledge of. The responses were coded as 1: practiced, 0: not practiced (Additional file 2).
Statistical analysis
Descriptive statistics related to a range of socio-demographic characteristics, knowledge, perceptions, and practices of mosquito LSM methods were calculated. Logistic regression model using enter method was used to identify factors associated with high-level knowledge of mosquito LSM methods. The model adjusted for gender and selected socio-demographic variables (excluding pregnancy status). All statistical analyses used SPSS version 18.
Ethical considerations
Ethical approval for this study was obtained from the Malawi National Health Science Research Committee (NHSRC) (Approval number: 2158).
Results
A total of 479 respondents, aged 16–81 years, participated in this study. Majority of them (64.5%) showed high-level knowledge of mosquito LSM methods (Table 1). Table 2 shows household knowledge, perceptions and practices regarding specific mosquito LSM methods. A small proportion of the respondents (5.2 %) had knowledge of larviciding. About 65.6% of the respondents had knowledge regarding draining stagnant waters as a malaria control method. Some 63.7 % (200/314) of the respondents had positive perceptions regarding draining stagnant waters while 39.8% (101/254) had positive perceptions regarding clearing grass/bushes as the most effective method for malaria control. It was observed that 90.2% (229/254) and 95.3% (223/234) of the respondents practiced malaria control by clearing grasses/bushes and clean environment around the home, respectively.
Table 1
Socio-demographic factors of respondents and their levels of knowledge regarding mosquito LSM methods in Nthache area, Mwanza district
Characteristics
N = 479
n (%)
Sex
Male
140 (29.2)
Female
339 (70.8)
Age-group (years)a
≤ 35 years-old
273 (57.0)
> 35 years-old
202 (42.2)
Marital status
Married
379 (79.1)
Single
22 (4.6)
Widowed
41 (8.6)
Divorced/separated
37 (7.7)
Education status
Primary
307 (64.1)
None
111 (23.2)
Secondary
56 (11.7)
Informal/pre-primary
5 (1.0)
Pregnancy status (women-of-child-bearing-age between 15–49 years-old)
N = 276
Not-pregnant
258 (93.5)
Pregnant
18 (6.5)
Occupation
Crop farming
286(59.7)
Mixed-farming (crop and livestock)/pastoralist
93 (19.4)
Business/self-employed
42 (8.8)
Employee
25 (5.2)
Housewife
22 (4.6)
Unemployed/student
7 (1.5)
Other
4 (0.8)
Household ownership
Owned
466 (97.3)
Rented
13 (2.7)
Household floor
Natural/earth
398 (83.1)
Cement/tiles
81 (16.9)
Household roof
Grass/thatch
292 (61.0)
Iron-sheets
187 (39.0)
Household wall
Brickwall
344 (71.8)
Mudwall
135 (28.2)
Household energy used
Firewood
433 (90.4)
Charcoal
46 (9.6)
Levels of knowledge regarding mosquito larval source management methods
High
309 (64.5)
Low
170 (35.5)
aAge of 4 (0.8 %) respondents were missing in the dataset
Table 2
Knowledge, perceptions and practices regarding specific mosquito LSM methods among respondents in Nthache area, Mwanza district
Household knowledge
N = 479
n (%)
Knowledge about draining stagnant water
314 (65.6)
Knowledge about larviciding
25 (5.2)
Knowledge about clearing grass/bushes
254 (53.0)
Knowledge about clean environment
234 (48.9)
Household practices
Practices regarding draining stagnant water
N = 314
270 (86.0)
Practices regarding larviciding
N = 25
8 (32)
Practices regarding clearing grass/bushes
N = 254
229 (90.2)
Practices regarding clean environment
N = 234
223 (95.3)
Household perceptions
Positive-perceptions regarding draining stagnant water
Table 3 shows the results of factors associated with high-level knowledge of mosquito LSM methods among respondents in Nthache, Mwanza. Compared to respondents with primary education, those with secondary education were more likely, whereas those without education were less likely, to have high-level knowledge of mosquito LSM methods (AOR = 3.54, 95% CI 1.45–8.63, P = 0.005 and AOR = 0.38, 95% CI 0.23–0.64, P = 0.000, respectively). Compared to respondents engaged in crop farming, those engaged in mixed farming (including pastoralists) and the self-employed (including business persons) were more likely to have high-level knowledge of mosquito LSM methods (AOR = 6.95, 95% CI 3.39–14.23, P = 0.000 and AOR = 3.61, 95% CI 1.47–8.86, P = 0.005, respectively). Respondents living in mud-walled households were less likely to have high-level knowledge of mosquito LSM methods than those living in brick-walled households (AOR = 0.50, 95% CI 0.30–0.86, P = 0.011).
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Table 3
Factors associated with high-level knowledge regarding mosquito LSM methods among respondents in Nthache area, Mwanza district
Factors
Categories
High-level knowledge
COR
95% CI
AOR
95% CI
P-value
Sex
Female
1.00
Ref
1.00
Ref
Male
1.35
0.89–2.06
1.08
0.65–1.77
0.772
Marital status
Married
1.00
Ref
1.00
Ref
Single
0.85
0.35–2.08
0.43
0.13–1.38
0.155
Widowed
0.38
0.20–0.73
0.74
0.33–1.67
0.468
Divorced/separated
0.71
0.36–1.42
0.89
0.42–1.89
0.757
Education status
Primary
1.00
Ref
1.00
Ref
Secondary
3.38
1.48–7.73
3.54
1.45–8.63
0.005
None
0.40
0.25–0.62
0.38
0.23–0.64
0.000
Informal/pre-primary
0.73
0.12–4.41
0.92
0.13–6.86
0.939
Occupation
Crop farming
1.00
Ref
1.00
Ref
Mixed-farming/pastoralist
5.55
2.83–10.85
6.95
3.39–14.23
0.000
Business/self-employed
3.72
1.60–8.66
3.61
1.47–8.86
0.005
Unemployed/student
0.56
0.12–2.54
0.57
0.10–3.22
0.523
Employed
0.95
0.42–2.16
0.88
0.36–2.11
0.768
Housewives
0.62
0.26–1.48
0.58
0.22–1.52
0.267
Other
0.25
0.03–2.41
0.32
0.03–3.62
0.359
Household wall
Brickwall
1.00
Ref
1.00
Ref
Mudwall
0.52
0.34–0.78
0.50
0.30–0.86
0.011
Household floor
Natural/earth
1.00
Ref
1.00
Ref
Cement/tiles
1.99
1.15–3.47
1.30
0.65–2.60
0.466
Household roof
Grass/thatch
1.00
Ref
1.00
Ref
Iron sheets
1.62
1.10–2.41
1.17
0.67–2.04
0.590
Multivariate model adjusted for sex, marital status, education status, occupation, household wall, household floor and household roof. Age-group (years), pregnancy status, household ownership and energy type were not significant at bivariate level
Italic values indicate significance of p value (p ≤ 0.05)
Discussion
The purpose of this study was to assess knowledge, perceptions and practices of mosquito LSM methods to guide the design and implementation of effective malaria control interventions in rural Malawian communities. A high-level knowledge of mosquito LSM methods was observed in the study population. This finding was in contrast with a Tanzanian study that reported few respondents in the community had knowledge of the usefulness of mosquito LSM methods in malaria control [17]. This was due to failure by policy makers and implementers to prioritize methods in Tanzanian rural areas [17]. This study’s findings further showed that respondents without education were less likely to have high-level knowledge of mosquito LSM methods than those with primary education, a finding similar to a Cameroonian study that showed that literate people had a better understanding of malaria messages through formal education and media [18]. However, a Ghanaian study showed no significant association between education level and knowledge of malaria prevention [19]. Hence, non-formal and informal education was recommended for malaria control-related health promotion interventions. There is need to raise community awareness of mosquito LSM methods among non-literate people. According to Mukabana et al., community-based educational programmes for larval control should be communicated through personal interaction based on learning-by-doing [17]. These educational programmes have the potential to change the health status through new knowledge gained, changing perceptions, gaining and practicing new skills and behaviour [20]. A lack of incentives, labour-intensiveness and the time-demanding nature of LSM activities were barriers to community participation in Malawi [12].
This study showed a very low proportion of respondents with knowledge of larviciding as a malaria control method, similar to a study in east-central Tanzania that showed that majority of respondents were unaware of larviciding [17]. This was attributed to the fact that larviciding programmes were limited and restricted to urban areas, so that rural people were unaware of it [17]. There is need for health promotion interventions in rural areas to include larviciding. The present study’s results showed that close to two-thirds of respondents had knowledge of draining stagnant water as a malaria control method. This was comparable to an Ethiopian study that found that 84.2% of the respondents knew of draining stagnant water as a malaria control method [21]. Both results indicate inadequate knowledge among respondents regarding draining stagnant water as a malaria control method. This calls for increased awareness of this method in SSA where malaria is prevalent, including Malawi.
Compared to respondents engaged in crop farming, the self-employed (including business persons) and those engaged in mixed farming (including pastoralists) were more likely to have high-level knowledge of mosquito LSM methods. Further, a study in Tanzania observed that some aagricultural activities generate larval habitats whereas others control malaria [22]. Mboera et al. observed limited knowledge of human activities that contribute to malaria transmission among rural Tanzanian farmers [22]. This could explain why crop farmers in this Malawi study were unlikely to have high-level knowledge of mosquito LSM methods. Special consideration should be given to crop farmers when designing and implementing mosquito LSM methods programmes.
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Imbahale et al. developed a basic socio-economic indicator based on information on the type of house owned [14]. The lowest indicator was associated with traditional houses (grass-thatched and mud-walled) [14]. The findings in this Malawian study suggested that respondents living in mud-walled households were less likely to have high-level knowledge of mosquito LSM methods than those living in brick-walled households. However, an American study observed that respondents from low-income households were more highly motivated to control mosquitoes than those from high-income households [23]. Hence, it is necessary to target both low- and high-income households with malaria prevention and control-related health promotion interventions to improve knowledge, perceptions and practices. Here, this study observed that few respondents had positive perceptions for larviciding as a malaria control method. Acceptability of larviciding was affected by poor perceptions about its safety in east-central Tanzania [17]. Safety in larviciding in rural areas should be prioritized.
As to limitations, firstly, associations derived from cross-sectional studies fell short of establishing temporal relationship between factors and outcomes of the study. Secondly, it is possible that those individuals with knowledge of mosquito LSM methods may not have been adult members of households that answered the questionnaires. Thirdly, data collection was done during the rainy season when malaria was prevalent, and when respondents could have been exposed to messages on mosquito LSM methods that influenced their responses. It is, therefore, important to generalize these results with caution as they may not necessarily reflect knowledge, perceptions and practices of mosquito LSM methods in Malawi.
Conclusions
This study established a high-level knowledge of mosquito LSM methods. Besides education, a well-known predictor of high-level knowledge of mosquito LSM methods, occupation and socio-economic status were also identified as predictors. Therefore, the uneducated, crop farmers and poor households should be considered when designing and implementing this strategy. Larviciding was the least known mosquito LSM method, and it is therefore important to promote awareness and practice of larviciding in rural communities. Positive perceptions for clearing grass/bushes and larviciding were low. Health workers should focus on targeted health promotion interventions regarding mosquito LSM methods.
Acknowledgements
Authors would like to thank the respondents that participated in the study and Hassan Mdala who designed the map for the study area. Further, the authors are highly indebted to Dr. Leonard Mboera of Tanzania National Institute for Medical Research (NIMR) for granting them permission to adapt household’s survey questionnaire used in Mvomero district, Tanzania.
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Ethics approval and consent to participate
The study was approved by the Malawi National Health Science Research Committee (NHSRC) at Ministry of Health (NHSRC approval number: 2158).
Competing interests
The authors declare that they have no competing interests.
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Household knowledge, perceptions and practices of mosquito larval source management for malaria prevention and control in Mwanza district, Malawi: a cross‐sectional study
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