The effectiveness of a nationwide universal coverage campaign of insecticide-treated bed nets on childhood malaria in Malawi

Abstract

Abstract Background Although the universal coverage campaign of insecticide-treated mosquito bed nets (ITNs) has been associated with improved malaria outcomes, recent reports indicate that the campaign is losing its sparkle in some countries. In Malawi, the universal coverage campaign was implemented in 2012, but its impacts are yet to be ascertained. Thus, this study examined the effects of the campaign on malaria morbidity among children in Malawi. Methods This is a repeated cross-sectional study. The study used nationally-representative malaria indicator survey (MIS) data collected in 2012 and 2014. In total, the analysis included 4193 children between the ages of 6 and 59 months (2171 from 2012 MIS and 2022 from 2014 MIS). ITNs coverage and malaria morbidity before (2012 = pre-test/control) and after (2014 = post-test/treated) the universal coverage campaign of ITNs were compared. The treated and control samples were matched on measured relevant covariates using propensity scores. Results The mean number of ITNs per household improved significantly from 1.1 (SD 1.0) in 2012 to 1.4 (SD 1.1) in 2014 (p

Full text

Zamawe et al. Malar J (2016) 15:505
DOI 10.1186/s12936-016-1550-9
RESEARCH
The eectiveness ofa nationwide
universal coverage campaign
ofinsecticide-treated bed nets onchildhood
malaria inMalawi
Collins O. F. Zamawe, Kanan Nakamura, Akira Shibanuma* and Masamine Jimba
Abstract
Background: Although the universal coverage campaign of insecticide-treated mosquito bed nets (ITNs) has been
associated with improved malaria outcomes, recent reports indicate that the campaign is losing its sparkle in some
countries. In Malawi, the universal coverage campaign was implemented in 2012, but its impacts are yet to be ascer-
tained. Thus, this study examined the effects of the campaign on malaria morbidity among children in Malawi.
Methods: This is a repeated cross-sectional study. The study used nationally-representative malaria indicator sur-
vey (MIS) data collected in 2012 and 2014. In total, the analysis included 4193 children between the ages of 6 and
59 months (2171 from 2012 MIS and 2022 from 2014 MIS). ITNs coverage and malaria morbidity before (2012 = pre-
test/control) and after (2014 = post-test/treated) the universal coverage campaign of ITNs were compared. The
treated and control samples were matched on measured relevant covariates using propensity scores.
Results: The mean number of ITNs per household improved significantly from 1.1 (SD 1.0) in 2012 to 1.4 (SD 1.1) in
2014 (p < 0.001). Nonetheless, the prevalence of malaria among children increased considerably from 27.7 % (2012) to
32.0 % (2014) (p = 0.002). The risk of malaria was also significantly higher in 2014 compared to 2012 (RR = 1.14; 95 %
CI 1.01–1.29). Besides, the use of bed nets was not significantly associated with malaria morbidity in 2014 (RR = 0.92;
95 % CI 0.76–1.12), but it was in 2012 (RR = 0.83; 95 % CI 0.70–1.00).
Conclusions: The universal coverage campaign of ITNs was not associated with a reduced burden of malaria among
children in Malawi. This was likely due to increased insecticide resistance, inconsistent use of bed nets and under-uti-
lization of other methods of malaria control. This calls for a multifaceted approach in the fight against malaria instead
of simple dependence on ITNs. In particular, local or community level malaria interventions should go hand in hand
with the universal coverage campaign.
Keywords: Malaria, Insecticide-treated bed nets, Children, Plasmodium falciparum
© 2016 The Author(s). This article is distributed under the terms of the Creative Commons Attribution 4.0 International License
(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium,
provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license,
and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/
publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Background
e global incidence and mortality rate of malaria have
fallen by 37 and 58%, respectively in the last decade [1].
Nevertheless, malaria is still a major life-threatening dis-
ease in the world. For instance, almost half of the world’s
population (3.3 billion) remains at risk of being infected
with malaria and over 200 million cases of malaria and
438,000 malaria attributable deaths were reported in
2015 [2]. Globally, children aged under-five years are
the most susceptible group to malaria [1, 2]. Malaria
kills a child every minute and accounts for one-sixth of
all childhood deaths in high malaria transmission areas
[3]. In 2013, around 80% of the malaria deaths occurred
among under-five children [4].
Open Access
Malaria Journal
*Correspondence: shibanuma@m.u-tokyo.ac.jp
Department of Community and Global Health, Graduate School
of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku,
Tokyo 113-0033, Japan
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Zamawe et al. Malar J (2016) 15:505
e World Health Organization (WHO) recog-
nizes five key interventions for preventing and treating
malaria. ese are prompt diagnosis and effective treat-
ment of malaria, the use of insecticide-treated mosquito
nets (ITNs) or long-lasting insecticidal nets (LLINs),
indoor residual spraying, chemo-prevention and inter-
mittent preventive therapy for pregnancy/infancy [5].
Since malaria is largely transmitted through mosquito
bites, the use of ITNs is the most popular, practical and
cost-effective intervention [6, 7]. Evidence is available
to show that ITNs can save about six lives each year for
every 1000 children [8].
e burden of malaria is heaviest in low income coun-
tries [2]. e recent world malaria report indicates that
about 80% of the global malaria cases and deaths in 2013
occurred in Africa, particularly in the sub-Saharan region
[2]. Additionally, malaria is also one of the top ten causes
of mortality in low income countries [2, 9]. erefore,
to ensure that all those at risk of malaria are protected
(especially in malaria endemic countries), WHO recom-
mended universal access to ITNs [10, 11].
Malawi is one of the malaria endemic countries. It is
among the 18 high-risk countries accounting for 90% of
the estimated number of Plasmodium falciparum infec-
tions in sub-Saharan Africa [2]. Almost everyone in
Malawi is at risk of malaria (>1 case/1000 population)
[2]. In particular, about six million suspected malaria
cases are treated each year and malaria is the number
one cause of morbidity and mortality in the country [12].
Of the suspected malaria cases, about 50% occur among
under-five children [12]. Malaria is also responsible for
about 40 % of the under-five children hospitalization
annually [12, 13].
An ITN policy has been at the centre of malaria con-
trol in Malawi since 2006 [13]. In the first few years, the
focus was on free distribution of ITNs to all under-five
children and pregnant women during their first visit to
a health facility/antenatal care [13, 14]. is approach
proved insufficient to achieve the universal coverage of
ITNs [14]. For that reason, a nationwide mass distribu-
tion of ITNs (hereinafter universal coverage campaign)
was implemented in 2012 [12]. e goal was to have 90%
of all households owning at least one ITN and achieve a
net utilization rate of 80% [12]. About 5.6 million ITNs
were distributed across the country [12, 13]. e cam-
paign reached 87 % of the people who were registered
and the number of persons per net ranged from 1.6 to
2.4. Specific details of the campaign, including logistics in
the field are described elsewhere [12].
Even though the universal coverage campaign is evi-
dence driven and has been shown to reduce malaria-
associated morbidity and mortality [8, 15, 16], recent
reports suggest that the campaign is losing its sparkle in
some countries. In Burkina Faso, for instance, childhood
malaria increased after the campaign [17]. Similarly,
the scale-up of ITN coverage was not associated with
decreased incidence of malaria in Zambia and Mali [18,
19]. Considering that huge amount of resources are being
channelled towards the universal coverage campaign [2,
13], it is critical to understand how increased access to
ITNs relates to the population health. is would ensure
efficient use of the limited resources in the fight against
malaria. So far, the effect of the universal coverage cam-
paign in Malawi has not been ascertained. erefore, this
study examined the effectiveness of the universal cover-
age campaign on malaria morbidity among under-five
children in Malawi.
Methods
Study design anddata
is is a repeated cross-sectional study. Nationally rep-
resentative data collected in 2012 and 2014 through the
malaria indicator survey (MIS) were used. In 2012, the
MIS was conducted from April to May [20]. is was just
before the universal coverage campaign—though about
500,000 of the 5.6 million ITNs had already been distrib-
uted. e 2014 MIS was undertaken from May to June
[21]. us, the 2012 and 2014 surveys were carried out
around the same time of the year. In this study, bed net
coverage and malaria morbidity among under five chil-
dren before and after the universal coverage campaign
were compared.
Overview ofthe MIS: objectives, population andsampling
e MIS is a nationally representative cross-sectional
study that is periodically conducted as part of the
national malaria surveillance program in malaria bur-
dened countries [20, 21]. In Malawi, the key objectives of
MIS are to (a) monitor and evaluate the coverage and use
of malaria control interventions, (b) assess knowledge,
attitudes, and practices of malaria and (c) measure the
prevalence of fever, malaria and anaemia among children
[20, 21]. e survey is implemented by the Ministry of
Health through the National Malaria Control Programme
[20, 21].
In 2012 and 2014, MIS collected data from 3404 to
3405 households, respectively. ese households were
identified through a two-stage cluster sampling method.
e first stage involved selecting 140 clusters (or enumer-
ation areas) out of about 12,474 by means of probability
proportional to size. In the second stage, 25 households
were selected from each chosen cluster using a system-
atic random sampling approach. All women of repro-
ductive age (15–49 years) and children aged between
6 and 59 months (hereinafter children) in the selected
households were eligible to participate. For the children,
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Zamawe et al. Malar J (2016) 15:505
malaria and haemoglobin tests were conducted in the
field and a thick blood smear was taken for a confirma-
tory malaria parasite laboratory test.
Data analysis andstatistical procedures
MIS 2012 and 2014 children’s datasets were pooled.
ese datasets also contained information about the chil-
dren’s mothers. In total, 4193 children were included in
the analysis (2171 from 2012 MIS and 2022 from 2014
MIS). Variables wereincluded in the analysis based on
their relevance to the study objectives.e outcome vari-
able was malaria status (positive or negative) based on
confirmed laboratory results. Key covariates included
‘child slept under a bed net’ (‘yes’ if the child slept under
bed net the night before the survey, otherwise ‘no’), num-
ber of bed nets per household and social-demographic
characteristics of the child and his/her mother.
e analysis proceeded in three stages. First, descrip-
tive statistics were computed and the predictors of
malaria in 2012 and 2014 were separately examined. In
particular, Chi-squared tests for independence were per-
formed and multivariable logistic regression modelswere
fitted. e level of significance was 5% and we used 95%
confidence interval (CI). In each year (2014/2012), the
urban–rural ratio of the selected clusters was not propor-
tional to the population distribution in Malawi. For that
reason, sample weights were used to make the data rep-
resentative of the entire population [20, 21].
e second stage involved examining the impact of
ITN scale-up on childhood malaria. e universal cov-
erage campaign was the treatment variable or interven-
tion. is study compared malaria morbidity before
(2012= control/pre-test) and after (2014= treatment/
post-test) the intervention. e 2012 and 2014 samples
were matched using propensity scores to correct for
selection bias [22]. e treated (2014) were matched with
the control (2012) on the following covariates using a cal-
iper of 0.001 [23]: age of the child, sex of the child, area
of residence, cluster attitude, wealth index score, sex of
the household head, years of education (mother), num-
ber of under five children (household), number of house-
hold members, literacy (mother) and mother’ access to
malaria messages. Standardized differences (0.10 cut-off
point) were used to evaluate how well the treated and
control groups were balanced in the matched samples
[23, 24]. Propensity score matching (PSM) minimized
systematic differences between samples to acceptable
levels (see Additional file1). In addition to estimating the
overall treatment effect, the samples were also stratified
into rural and urban (area of residence).
Lastly, this study assessed the effect of ITNs on malaria
morbidity. e use of bed net was the treatment vari-
able or intervention. Malaria morbidity was compared
between children who slept under a bed net (treated) and
those who did not (control) after correcting for selection
bias through PSM [22]. In 2014, data concerning the use
of bed nets were available for 1934 out of 2022 partici-
pants. Of these, 1411 (73.0%) used bed nets (treated) and
523 (27.0%) did not (control). In 2012, the sample con-
sisted of 2171 participants. However, data regarding the
use of bed nets were available for 2011 participants, of
whom 1238 (61.6%) slept under a bed net (treated) and
773 (38.4%) did not (control). e participants for each
year were matched separately (see Additional file2) using
the same specifications as in stage two above. All analyses
were performed using Stata 13.1 (StataCorp LP, Texas,
USA).
Ethics statement
e MIS data and permission to use it were obtained
from the demographic health survey (DHS) program.
Besides, the study protocol was reviewed and approved
by the Research Ethics Committee of the University of
Tokyo. e original study obtained ethical clearance from
the Malawi’s National Health Sciences Research Com-
mittee (NHSRC). Mothers provided verbal informed
consents for their children’s haemoglobin and malaria
tests [20, 21].
Results
e coverage and use of ITNs increased between 2012
and 2014 in Malawi. More precisely, the mean num-
ber of ITNs per household improved significantly from
1.1 (SD 1.0) in 2012 to 1.4 (SD 1.1) in 2014 (p<0.001).
e proportion of children who had at least one mos-
quito net also increased from 70.8 to 78.4% during the
same period (p<0.001). Similarly, the proportion of chil-
dren who slept under a bed net increased from 62.1%
(2012) to 69.4 % (2014) (p < 0.001). Notwithstanding,
the national prevalence of malaria parasite among chil-
dren increased considerably from 27.7% (2012) to 32.0%
(2014) (p= 0.002). Figure1 depicts ITN coverage, bed
net use and malaria morbidity in 2012 and 2014. Social
and demographic particulars of the participants in 2012
and 2014 with respect to malaria outcomes are described
in Table1.
Besides, the determinants of malaria morbidity among
children were examined. In 2012, the odds of being
infected with malaria were significantly lower among
children who slept under a bed net than those who did
not (AOR=0. 65; 95% CI 0.47–0.89). In contrast, sleep-
ing under bed net was not a significant predictor of
malaria in 2014 (AOR=0.77; 95% CI 0.57–1.06). In both
years, the number of bed nets per household was not
significantly associated with malaria morbidity among
children. Table 2 presents the predictors of childhood
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Zamawe et al. Malar J (2016) 15:505
malaria in 2012 and 2014, including all the variables that
were included (adjusted for) in the models.
Furthermore, the effect of ITN scale-up on childhood
malaria in Malawi was examined using the matched data.
Particularly, this study compared malaria morbidity in
2014 (treatment) and 2012 (control). Overall, the risk of
malaria was 14% higher in 2014 than 2012 (RR=1.14;
95% CI 1.01–1.29). Said differently, Malawian children
were at a significantly greater risk of malaria after the
universal coverage campaign than before (Table3).
In addition, this study also investigated the impact of
using bed nets on malaria outcomes among children in
2012 and 2014. In 2014, the overall risk of malaria was
lower among children who used bed nets compared to
those who did not (RR=0.92; 95% CI 0.76–1.12). How-
ever, the result was not statistically significant, even
after stratification by areas of residence (rural/urban).
In contrast, the use of bed nets in 2012 was significantly
associated with decreased risk of childhood malaria
(RR=0.83; 95% CI 0.70–1.00). Detailed results are pro-
vided in Table3.
Discussion
ere are three key findings from this study. First, the
2012 universal coverage campaign improved both bed
net coverage and use among children in Malawi. Sec-
ondly, the use of bed nets was significantly associated
with reduced risk of childhood malaria in 2012, but not
in 2014. is simply suggests that ITNs were relatively
ineffective after the 2012 universal coverage campaign in
Malawi. Lastly, the prevalence of malaria among children
in Malawi was higher in 2014 than 2012. In other words,
the universal coverage campaign was not associated with
improved malaria outcomes.
Improved access to ITNs between 2012 and 2014 was
not associated with reduced malaria morbidity among
children in Malawi. is finding challenges the current
public health understanding that the universal cover-
age campaign reduces the burden of malaria [8, 25–27].
Until now, the effects of ITN scale-up have been uneven.
For example, malaria morbidity/mortality declined in
south-west Cameroon, rural Tanzania and Rwanda after
the coverage of ITNs was enhanced [28–30]. In con-
trast, higher/unchanged malaria prevalence/mortality
were reported in Zambia, Burkina Faso, Mali and west-
ern Myanmar following the ITN scale-up [17, 19, 31]. In
some cases, better access to ITNs was accompanied by
reduced incidence of malaria at the outset, but the gains
could not be sustained [32, 33]. ese variations could
be because most of the studies were confined to a par-
ticular population or setting in their respective countries
[31, 34]. is study analysed nationally representative
data with a special focus on children. As such, the results
provide a richer or wider perspective of the impact of the
universal coverage campaign.
Besides, ITN usage had an inconsequential impact on
malaria morbidity in Malawi, especially after the univer-
sal coverage campaign. As noted, the use of ITNs pro-
vided substantial protection against childhood malaria in
2012, but the effects attenuated and became insignificant
in 2014. e rise of insecticide resistance among Anoph-
eles mosquitoes is one of the plausible reasons for this
phenomenon [35, 36]. is hypothesis concurs with the
findings of a study in Malawi, which has recently reported
that there is reduced efficacy of bed nets in the country as
a consequence of increased intensity of insecticide resist-
ance [37]. Related outcomes have also been reported by
another study in Mozambique, which has clearly shown
that resistance to pyrethroids is extremely high in the
country [36]. erefore, amid serious concerns of insec-
ticide resistance, the universal coverage campaign may
not effectively reduce the burden of malaria in affected
countries.
Comparable studies have attributed the reduced effi-
cacy of ITNs to the community-wide effects of ITNs [17,
28, 38]. e reasoning is that ITNs do not only protect
individuals from direct mosquito bites, they also kill
the mosquitoes and thereby protecting from malaria
even those who do not sleep under bed nets [38]. us,
increased ITN coverage reduces to a greater extent the
swarm of mosquitoes in an area and in so doing protect-
ing from malaria more and more people with no access
to ITNs. is notion provides an alternative explanation
about why malaria morbidity was not significantly differ-
ent between users and non-users of bed nets after ITN
scale-up in Malawi. Nonetheless, the community-wide
effects of ITNs fall short of elucidating the impact of
the universal coverage campaign in Malawi. In general,
the campaign increased ITN coverage and this suggests
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
ITN ownership Slept under bed netMalaria morbidity
MIS2012 MIS2014
Fig. 1 2012 and 2014 trends in ITN coverage and childhood malaria
in Malawi (n = 4495—weighted). MIS malaria indicator survey, ITN
insecticide treated bed net
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Zamawe et al. Malar J (2016) 15:505
relatively far-reaching community-wide effects. As a
result, malaria prevalence was not supposed to increase
in 2014.
Knowledge about the causes of malaria (i.e. mosquito
bites can cause malaria) and malaria prevention/control
strategies (i.e. sleeping under ITNs prevents malaria)
decreased among the children’s mothers between 2012
and 2014 in Malawi. Existing literature point out that
knowledge of malaria transmission and prevention is
associated with regular use of ITNs [39–41]. Accordingly,
inconsistent use of ITNs was bound to be greater in 2014.
Since the success of the universal coverage campaign
Table 1 Under ve children malaria morbidity in 2012 and 2014 by socio demographic characteristics (weighted,
unmatched)
SD standard deviation, KM kilometres, ITN insecticide-treated bed net
* Signicant (p≤0.05); ** non signicant (p>0.05)
Variable name Category Year=2012 (n=2312) Year=2014 (n=2183)
Malaria test outcome Malaria test outcome
Total Negative Positive p value Total Negative Positive p value
Age of the child (months) Mean (SD) 31.4 (15.3) 30.5 (15.2) 34.5 (15.1) <0.001* 30.9 (15.3) 30.0 (15.5) 35.1 (14.9) <0.001*
Sex of the child Female 1001 (52.9 %) 769 (53.0 %) 300 (54.0 %) 0.955** 1111 (50.9 %) 665 (51.5 %) 289 (47.4 %) 0.149**
Male 892 (47.1 %) 681 (47.0 %) 255 (46.0 %) 1072 (49.1 %) 626 (48.5 %) 319 (52.6 %)
Area of residence Rural 2009 (86.9 %) 1211 (83.5 %) 527 (95.0 %) <0.001* 1862 (85.3 %) 1052 (81.5 %) 582 (95.8 %) <0.001*
Urban 303 (13.1 %) 239 (16.5 %) 28 (5.0 %) 321 (14.7 %) 239 (18.5 %) 25 (4.2 %)
Cluster attitude (KM) Mean (SD) 0.9 (0.3) 0.9 (0.3) 0.9 (0.3) 0.169** 0.9 (0.3) 1.0 (0.0) 0.9 (0.0) 0.001*
Child slept under bed net No 810 (37.9 %) 492 (36.6 %) 228 (44.2 %) <0.001* 637 (30.6 %) 353 (28.3 %) 224 (39.2 %) 0.016*
Yes 1327 (62.1 %) 852 (63.4 %) 288 (55.8 %) 1444 (69.4 %) 891 (71.7 %) 347 (60.8 %)
Sex of household head Female 497 (21.5 %) 319 (22.0 %) 115 (20.7 %) 0.632** 320 (14.7 %) 194 (15.0 %) 93 (15.4 %) 0.398**
Male 1815 (78.5 %) 1130 (78.0 %) 440 (79.3 %) 1863 (85.3 %) 1098 (85.0 %) 513 (84.6 %)
Age of the mother (years) Mean (SD) 28.4 (6.7) 28.2 (6.5) 28.3 (6.9) 0.863** 28.0 (6.5) 28.1 (6.4) 28.4 (6.7) 0.411**
Wealth index score Mean (SD) 2.8 (1.4) 3.3 (1.5) 2.5 (1.3) <0.001* 2.8 (1.4) 3.3 (1.4) 2.5 (1.3) <0.001*
Mother’s total years of
education Mean (SD) 4.8 (3.6) 5.8 (3.8) 3.9 (3.1) <0.001* 5.4 (3.7) 6.3 (3.6) 4.7 (3.2) <0.001*
Number of under five
children (mother) Mean (SD) 1.7 (0.7) 1.7 (0.7) 1.8 (0.7) 0.004* 1.7 (0.7) 1.6 (0.6) 1.7 (0.7) 0.002*
Number of bed nets
(household) Mean (SD) 1.1 (1.0) 1.2 (1.1) 0.9 (0.9) <0.001* 1.4 (1.1) 1.6 (1.1) 1.4 (1.1) 0.001*
Child’s mother can read No 846 (36.6 %) 474 (32.7 %) 262 (47.1 %) <0.001* 682 (31.2 %) 354 (27.4 %) 253 (41.6 %) <0.001*
Yes 1466 (63.4 %) 976 (67.3 %) 293 (52.9 %) 1501 (68.8 %) 938 (72.6 %) 354 (58.4 %)
Mother heard messages
about malaria (<6 weeks
ago)
No 1586 (73.4 %) 973 (70.6 %) 407 (81.9 %) <0.001* 1593 (78.9 %) 938 (76.4 %) 455 (84.5 %) 0.203**
Yes 574 (26.6 %) 405 (29.4 %) 90 (18.1 %) 427 (21.1 %) 290 (23.6 %) 83 (15.5 %)
Mother knowns mosquito
bites cause malaria No 149 (6.9 %) 70 (5.1 %) 54 (10.8 %) <0.001* 286 (14.2 %) 153 (12.5 %) 94 (17.5 %) 0.084**
yes 2011 (93.1 %) 1307 (94.9 %) 443 (89.2 %) 1734 (85.8 %) 1074 (87.5 %) 444 (82.5 %)
Mother knows fever is the
main sign of malaria No 190 (8.8 %) 127 (9.2 %) 32 (6.5 %) 0.082** 266 (13.2 %) 167 (13.6 %) 44 (8.1 %) 0.020*
Yes 1970 (91.2 %) 1250 (90.8 %) 464 (93.5 %) 1754 (86.8 %) 1060 (86.4 %) 495 (91.9 %)
Mother knowns sleep-
ing under ITN prevents
Malaria
No 1187 (54.9 %) 755 (54.8 %) 283 (57.0 %) 0.245** 1514 (74.9 %) 890 (72.5 %) 422 (78.5 %) 0.023*
Yes 973 (45.1 %) 623 (45.2 %) 214 (43.0 %) 506 (25.0 %) 337 (27.5 %) 116 (21.5 %)
Mother knows mosquito
repellant prevents malaria No 2099 (97.2 %) 1333 (96.8 %) 490 (98.6 %) 0.064** 1991 (98.5 %) 1202 (97.9 %) 537 (99.8 %) 0.017*
Yes 61 (2.8 %) 11 (3.2 %) 7 (1.4 %) 29 (1.5 %) 26 (2.1 %) 1 (0.3 %)
Mother knowns mosquito
coil prevents malaria No 2114 (97.9 %) 1343 (97.5 %) 489 (98.5 %) 0.112** 2003 (99.2 %) 1214 (98.9 %) 535 (99.4 %) 0.800**
Yes 46 (2.1 %) 35 (2.5 %) 7 (1.5 %) 17 (0.8 %) 13 (1.1 %) 3 (0.6 %)
Mother knowns cutting
grass around house
prevents malaria
No 1950 (90.3 %) 1238 (89.8 %) 455 (91.6 %) 0.046* 1905 (94.3 %) 1145 (93.3 %) 519 (96.4 %) 0.059**
Yes 210 (9.7 %) 140 (10.2 %) 42 (8.4 %) 115 (5.7 %) 82 (6.7 %) 19 (3.6 %)
Mother knowns children are
vulnerable to Malaria No 275 (12.7 %) 159 (11.6 %) 85 (17.1 %) 0.002* 388 (19.2 %) 232 (18.9 %) 102 (19.0 %) 0.864**
Yes 1885 (87.3 %) 1218 (88.4 %) 411 (82.9 %) 1632 (80.8 %) 995 (88.1 %) 436 (81.0 %)
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Zamawe et al. Malar J (2016) 15:505
partly depends on stable use of ITNs by those at risk of
malaria, noncompliance might have contributed to the
increase in malaria morbidity among Malawian children
in 2014.
Furthermore, awareness of interventions that may
limit malaria transmission before sleep time (i.e. cutting
grass around the house, mosquito repellent and mos-
quito coil) was lower among the children’s mothers in
Table 2 Predictors ofmalaria morbidity inunder ve children (unmatched data)
CI condence interval, KM kilometres, ITN insecticide-treated bed net
* Signicant (p≤0.05); ** non signicant (p>0.05)
Variable Year 2012 Year 2014
AOR 95% CI p value AOR 95% CI p value
Child slept under bed net 0.65 0.47–0.89 0.007* 0.77 0.57–1.06 0.109**
Child is male 0.92 0.73–1.15 0.463** 1.15 0.92–1.44 0.215**
Age of the child 1.02 1.01–1.03 <0.001* 1.02 1.02–1.03 <0.001*
Residential area is urban 0.42 0.26–0.67 <0.001* 0.35 0.21–0.59 <0.001*
Cluster altitude (KM) 1.17 0.83–1.66 0.380** 0.54 0.37–0.77 0.001*
Wealth index score 0.87 0.79–0.96 0.004* 0.80 0.73–0.88 <0.001*
Age of the mother 0.98 0.96–1.00 0.017* 0.99 0.97–1.01 0.342**
Mother’s years of education 0.93 0.88–0.99 0.023* 0.97 0.92–1.00 0.240**
Mother can read 1.22 0.83–1.79 0.325** 0.88 0.61–1.28 0.501**
Number of under five children 1.21 1.04–1.42 0.015* 1.25 1.05–1.48 0.011*
Number of bed nets (household) 1.14 0.98–1.33 0.102** 0.93 0.81–1.08 0.367**
Male household head 1.11 0.84–1.46 0.464** 0.96 0.71–1.29 0.768**
Heard malaria messages (<6 months ago) 0.66 0.49–0.87 0.004* 0.79 0.58–1.07 0.126**
Mother knowns mosquito bites cause malaria 0.49 0.32–0.74 0.001* 0.90 0.64–1.25 0.521**
Mother knows fever is the main sign of malaria 1.70 1.08–2.69 0.023* 1.85 1.26–2.71 0.002*
Mother knowns ITN prevents malaria 1.17 0.92–1.48 0.205** 1.00 0.76–1.32 0.999**
Mother knows mosquito repellant prevents malaria 0.58 0.24–1.40 0.227** 0.22 0.04–1.29 0.094**
Mother knowns mosquito coil prevents malaria 1.33 0.56–3.20 0.517** 0.60 0.16–2.20 0.437**
Mother knowns cutting grass around house prevents malaria 0.86 0.58–1.27 0.451** 0.89 0.51–1.56 0.693**
Mothers knowns children are vulnerable to malaria 0.71 0.51–0.99 0.043* 1.32 0.98–1.78 0.071**
Table 3 The eects of the universal coverage campaign (UCC) ofITNs and the use ofbed nets on childhood malaria
inMalawi
RR risk ratio, ITNs insecticide-treated bed nets, CI condence interval
* Signicant (p≤0.05); ** non signicant (p>0.05)
Year/period Intervention Level ofanalysis Malaria outcomes RR (95% CI) p value
Control (n) Treatment (n)
negative Positive Negative Positive
2012 vs 2014 UCC of ITNs Overall 1359 381 1205 401 1.14 (1.00–1.29) 0.036*
2012 vs 2014 UCC of ITNs Rural 898 373 779 358 1.07 (0.95–1.21) 0.254**
2012 vs 2014 UCC of ITNs Urban 454 59 373 37 0.78 (0.53–1.16) 0.223**
2014 Bed net use Overall 313 115 682 224 0.92 (0.76–1.12) 0.399**
2014 Bed net use Rural 227 100 448 197 1.00 (0.82–1.22) 0.990**
2014 Bed net use Urban 96 5 110 7 1.21 (0.40–3.69) 0.740**
2012 Bed net use Overall 465 164 719 200 0.83 (0.70–1.00) 0.049*
2012 Bed net use Rural 304 140 451 168 0.86 (0.71–1.04) 0.119**
2012 Bed net use Urban 156 29 121 11 0.53 (0.28–1.03) 0.060*
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

Page 7 of 8
Zamawe et al. Malar J (2016) 15:505
2014 compared to 2012. Because of the limited protec-
tion provided by ITNs (usually during bed time only)
[42], supplementary interventions play a crucial role
in malaria control. In Kenya and Myanmar, for exam-
ple, ITNs offered incomplete protection against malaria
due to early biting habits of the vectors [31, 42]. Due to
low awareness, it is likely that additional malaria control
methods were relatively under-utilized in 2014 [43, 44].
is resonate calls for broader vector control strategies to
limit malaria transmission before bedtime [42].
Taken together, insecticide resistance and inadequate
knowledge of malaria transmission and prevention pose
a serious threat to the efficacy of ITNs and the future
of the universal coverage campaign. is highlights
the need to constantly monitor the level of insecticide
resistance and the effects of ITNs to ensure that all peo-
ple at risk of malaria are protected. Moreover, there is
an urgent need to intensify and regularly update resist-
ance management strategies. In the long run, alternative
insecticides should be identified or developed. An inte-
grated approach is called for to malaria control in lieu of
simple dependence on ITNs. In particular, effective local
malaria control strategies (i.e. fill in puddles and clear-
ing bushes around residential areas) should be preserved
and promoted in malaria endemic areas. Accordingly,
the universal coverage campaign should go hand in hand
with intensive community based malaria awareness
campaigns.
is study had limitations and strengths. First, both
2012 and 2014 MIS relied on reported data except for
malaria status. So, recall and social desirability biases
cannot be ruled out. e strengths of this study include
the use of nationally representative data with relatively
large sample sizes. Although each survey was cross-sec-
tional in nature, the pooling of the two datasets permitted
comparison of the study outcomes over time. Moreover,
PSM allowed to balance measured covariates across 2012
and 2014 samples [24]. us, the study design mimicked
some of the characteristics of a randomized controlled
trial [23].
Conclusions
e universal coverage campaign improved both the
access and use of bed nets among children between 2012
and 2014 in Malawi. Nonetheless, the campaign was not
associated with a reduced burden of malaria. is is likely
due to increased insecticide resistance, inconsistent use
of bed nets and under-utilization of other malaria con-
trol methods. ese observations accentuate the need for
a composite intervention in malaria control. us, while
applauding the massive contribution of ITNs in the fight
against malaria, it is important to recognize that a mul-
tifaceted approach is required to effectively reduce the
burden of malaria. To this end, the utility of local solu-
tions and community level approaches in malaria control
should be stressed.
Abbreviations
ITNs: insecticide-treated mosquito bed nets; LLINs: lost lasting insecticidal
treated mosquito bed nets; SD: standard deviation; CI: confidence interval;
PSM: propensity score matching; WHO: World Health Organization; MIS:
malaria indicator survey; DHS: demographic health survey; AOR: adjusted
odds ratio; RR: risk ratio.
Authors’ contributions
CZ and MJ conceived and designed the study. CZ, KN and MJ developed the
study protocol. CZ requested data from the DHS programme. CZ, AS and MJ
performed data analysis or provided guidance. CZ wrote the manuscript. All
authors read and approved the final manuscript.
Acknowledgements
Many thanks to the DHS programme team for allowing us to use the dataset
and the support they rendered during data cleaning and merging process. We
are also grateful to Chrispin Mandiwa for his contribution during the protocol
development and study design.
Competing interests
The authors declare that they have no competing interests.
Availability of data and materials
The datasets supporting the conclusions of this article are available upon
request from the Demographic Health Survey Programme Team http://www.
dhsprogram.com/data/available-datasets.cfm.
Ethics approval and consent to participate
Permission to use malaria indicator survey was obtained from the DHS
program. In addition, the study protocol was reviewed and approved by the
Research Ethics Committee of the University of Tokyo. All participants of the
primary studies provided informed consent.
Funding
Collins O.F Zamawe is a Monbukagakusho Scholar supported by the Japanese
Government.
Received: 4 May 2016 Accepted: 5 October 2016
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