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Systematic assessment of factors affecting the delivery, access and use of
interventions to control malaria in pregnancy in sub-Saharan Africa
Hill, J.A.
Publication date
2014
Document Version
Final published version
Link to publication
Citation for published version (APA):
Hill, J. A. (2014). Systematic assessment of factors affecting the delivery, access and use of
interventions to control malaria in pregnancy in sub-Saharan Africa. Dutch University Press.
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Chapter 3: Supplementary Appendix
Coverage of intermittent preventive treatment and insecticide-treated nets for the control of malaria
during pregnancy in sub-Saharan Africa: a synthesis and meta-analysis of national survey data,
2009-11
Table of Contents
1.
eSupplement 1
: Data sources to estimate number of births protected against malaria by
insecticide-treated nets or intermittent preventive treatment in sub-Saharan Africa for 2010
1.1.
eFigure 1
: Flow diagram on data sources to estimate number of births protected against malaria by
insecticide-treated nets or intermittent preventive treatment in sub-Saharan Africa for a hypothetical population in 2010,
and to estimate disbursement of funds for malaria control by external organizations per capita malaria exposed
persons per year per country in 2001-10
2.
eSupplement 2
: Correlation between insecticide-treated net use among women aged 15-49 years
and pregnant women
2.1.
eFigure 2
: Scatterplot of use of insecticide-treated net use among women aged 15-49 years versus pregnant
women in 56 national surveys in 32 sub-Saharan countries in 2001-11
3.
eSupplement 3
: Adjustment of confidence intervals for clustering
3.1.
eTable 3.1: Difference in standard error when adjusted for clustering for prevalence of coverage of intermittent
preventive treatment, insecticide-treated nets and antenatal clinic visits in pregnancy
3.2.
eTable 3.2: Difference in standard error when adjusted for clustering for risk ratios of socio-economic status,
education and location of residence when evaluating effect on intermittent preventive treatment or
insecticide-treated net use in pregnancy
4.
eSupplement 4
: Flow diagram for inclusion and exclusion of surveys
4.1.
eFigure 4
: Flow diagram for inclusion and exclusion of surveys for the review of coverage of malaria prevention
in pregnancy in sub-Saharan Africa, 2009-11
5.
eSupplement 5
: Use of malaria prevention in pregnancy in sub-Saharan Africa as reported in
national surveys, 2005-11
5.1.
eTable 5.1: Coverage of intermittent preventive treatment during pregnancy in sub-Saharan Africa as reported
in national surveys, 2005-11
5.2.
eTable 5.2
: Use of insecticide-treated nets during pregnancy in sub-Saharan Africa as reported in national
surveys, 2005-2011
6.
eSupplement 6
: Calculations of number of births covered by intermittent preventive treatment,
insecticide treated nets and antenatal care in 2010, sub-Saharan Africa
6.1.
eTable 6.1: Calculation of number of births protected by intermittent preventive treatment in sub-Saharan
Africa, projected for 2010
6.2.
eTable 6.2: Calculation of number of births covered by insecticide-treated nets and antenatal care in sub-Saharan
Africa, projected for 2010
6.3.
eTable 6.3: Calculation of number of births covered by at least one or two antenatal care visits in countries with
an intermittent preventive treatment policy, sub-Saharan Africa, projected for 2010
6.4.
eTable 6.4: Calculation of number of births protected by intermittent preventive treatment or insecticide-treated
nets in sub-Saharan Africa, projected for 2007 for countries with a survey in 2004-09 and 2009-11
7.
eSupplement 7
: Information on intermittent preventive treatment or insecticide-treated net use
from sub-Saharan countries with one or two surveys in 2000-11
7.1.
Figure 7.1
: Trends in intermittent preventive treatment coverage in pregnancy among fourteen sub-Saharan
countries with national information in 3 or more surveys
7.2.
eFigure 7.2
: Trends in twenty sub-Saharan countries with national information on intermittent preventive
treatment in pregnancy limited to 1 or 2 surveys
7.3.
eFigure 7.3
:
Meta-analysis of difference in intermittent preventive treatment coverage for 24 countries with >1
survey, Africa, 2000-11
7.4.
eFigure 7.4
: Trends in insecticide-treated net use in pregnancy among thirteen sub-Saharan countries with
national information in 3 or more surveys
7.5.
eFigure 7.5
: Trends in twenty-nine sub-Saharan countries with national information on insecticide-treated net
use in pregnancy limited to 1 or 2 surveys
7.6.
eFigure 7.6
: Meta-analysis of difference in coverage of insecticide-treated net use for 30 countries with >1 survey,
Africa, 2000-11
8.
eSupplement 8
: Forestplots for effect of socioeconomic, educational status, location of residence,
parity and age on intermittent preventive treatment coverage and insecticide-treated net use for
countries with surveys in 2009-11 and a data set available
8.1.
eFigure 8.1
: Effect of socioeconomic status on intermittent preventive treatment coverage, comparing highest two
wealth quintiles with lower 3 wealth quintiles, among sub-Saharan countries with surveys in 2009-11, random
effects analysis
8.2.
eFigure 8.2
: Effect of education on intermittent preventive treatment coverage, comparing any vs. no education,
among sub-Saharan countries with surveys in 2009-11, random effects analysis
8.3.
eFigure 8.3
: Effect of location of residence on intermittent preventive treatment coverage, comparing urban vs.
rural, among sub-Saharan countries with surveys in 2009-11, random effects analysis
8.4.
eFigure 8.4
: Effect of parity on intermittent preventive treatment coverage, comparing primiparae vs.
multiparae, among sub-Saharan countries with surveys in 2009-11, random effects analysis
8.5.
eFigure 8.5
: Effect of age on intermittent preventive treatment coverage, comparing less than 21 years vs. 21
years or older, among sub-Saharan countries with surveys in 2009-11, random effects analysis
8.6.
eFigure 8.6
: Effect of socioeconomic status on insecticide-treated net use in the previous night among pregnant
women, comparing highest two wealth quintiles vs. lower 3 wealth quintiles, among sub-Saharan countries with
surveys in 2009-11, random effects analysis
8.7.
eFigure 8.7
: Effect of education on insecticide-treated net use in the previous night among pregnant women,
comparing any education vs. none, among sub-Saharan countries with surveys in 2009-11, random effects
meta-analysis
8.8.
eFigure 8.8
: Effect of location of residence on insecticide-treated net use in the previous night among pregnant
women, comparing urban vs. rural residence, among sub-Saharan countries with surveys in 2009-11, random
effects analysis
8.9.
eFigure 8.9
: Effect of gravidity on insecticide-treated net use in the previous night among pregnant women,
comparing primigravidae vs. multigravidae, among sub-Saharan countries with surveys in 2009-11, random
effects analysis
8.10. eFigure 8.10
: Effect of age on insecticide-treated net use in the previous night among pregnant women,
comparing less than 21 years vs. 21 years or older, among sub-Saharan countries with surveys in 2009-11,
random effects analysis
9.
References
eSupplement 1: Data sources to estimate number of births protected against malaria by
insecticide-treated nets or intermittent preventive treatment in sub-Saharan Africa for
2010
eFigure 1: Flow diagram on data sources to estimate number of births protected against malaria by
insecticide-treated net (ITN) use or intermittent preventive treatment (IPTp) in sub-Saharan Africa for a
hypothetical population in 2010, and to estimate disbursement of funds for malaria control by external
organizations per capita malaria exposed persons per year per country in 2001-10
References
:
1-7National surveys sub-Saharan Africa:
Demographic and Health surveys1
Malaria Indicator Surveys2
Multiple Indicator Cluster Surveys3
-United Nations Population Division 2010 revised database4
-Dellicour et al 20105
-Gething et al 20106
Coverage IPTp, SP, and ITNs 2009-2011 by country
Organisation for Economic Co-operation and Development7
Disbursement of money for malaria control to sub-Saharan countries from international programmes and agencies in 2001-2010
Projected for 2010:
Number of malaria exposed births covered by IPTp and ITNs in sub-Saharan Africa
Disbursement of money for malaria control by external organizations per
capita malaria exposed persons per year per country (2001-2010)
-United Nations Population Division 2010 revised database4
-Gething et al 20106
Malaria exposed live and stillbirths by country for 2010
Malaria exposed population size 2001-2010 by country
Sources
Intermediate step
Outcome
eSupplement 2: Correlation between insecticide-treated net use among women aged
15-49 years and pregnant women
eFigure 2: Scatterplot of use of insecticide-treated nets (ITNs) among women aged 15-49 years versus
pregnant women in 56 national surveys in 32 sub-Saharan countries in 2001-11
Using national data from 56 surveys in 32 sub-Saharan countries between 2001 and 2011, we derived a linear
regression model which was used to estimate the ITN use in Mali, Somalia and Swaziland among pregnant
women. Using the formula in eFigure 2.1, the ITN use of 62.7% in Mali among women aged 15-49
corresponded to 66.8% among pregnant women; for Somalia the percentages were 20.9% and 23.1%,
respectively, and for Swaziland they were 3.8% and 5.2%.
y = 1.0454x + 1.269
R² = 0.9633
0
20
40
60
80
100
0
20
40
60
80
100
P
e
rcentag
e
IT
N
use among
preg
nant
women
Percentage ITN use among women aged 15-49 years
Linear Trendline
eSupplement 3: Adjustment of standard errors of prevalence and risk ratios for
clustering
eTable 3.1: Difference in standard error when adjusted for clustering for prevalence of coverage of IPT,
ITN and ANC in pregnancy
Prevalence
coverage No of surveys Median difference in standard error (IQR)
IPTp 33 0.0030 (0.0010-0.0050) ITN 41 0.0020 (0.0010-0.0040) ANC 1+ 45 0.0040 (0.0020-0.0103) ANC 2+ 35 0.0037 (0.0024-0.0100)
ANC: Antenatal clinic. IPT: intermittent preventive treatment. IQR: interquartile range. ITN: insecticide treated
nets.
Note: All national surveys that were used have in common that they use a cluster design. If this would not be
taken into account, the confidence intervals could be too narrow, because it would be assumed that each
person’s information is independent of each other, whereas information from persons in the same cluster may
have common factors. For surveys with a data set available the difference in standard error was calculated as the
difference in standard error from a model where simple random sampling was assumed and a model where
clustering was taken into account, and the median difference is presented in the table. For survey reports where
no data set was available, we calculated the standard error from the information available in the report, and
added the median difference in standard error as an estimate to take clustering into account. E.g. for Benin, the
proportion of women using IPTp was 0.228 (or 22.8%), and the sample size was 5130; the 95% confidence
interval was 0.2166 to 0.2398, and from this the standard error can be calculated (difference in 95% confidence
interval divided by 2*1.96) as 0.0059. Adding 0.003 for clustering, the adjusted standard error was 0.0089, and
the revised 95% confidence interval was 0.2104 to 0.2456 (or 21.0- 24.6%).
eTable 3.2: Difference in standard error when adjusted for clustering for risk ratio estimates of the effect
of socio-economic status, education and location of residence on IPTp or ITN use in pregnancy
Endpoint Risk ratios evaluated* No of surveys Median difference in standard error (IQR)
IPTp SES 35 0.0190 (0.0043-0.0272) IPTp Education 35 0.0073 (0.0004-0.0172) IPTp Residence 35 0.0261 (0.0094-0.0605) ITN SES 38 0.0112 (0.0005-0.0225) ITN Education 36 0.0051 (0.0000-0.0132) ITN Residence 38 0.0188 (0.0027-0.0372)
IPTp: intermittent preventive treatment in pregnancy. IQR: interquartile range. ITN: insecticide treated nets.
SES: socioeconomic status.
*SES: comparing two highest vs. three lower wealth quintiles; Education: comparing any vs. no education;
Residence: comparing urban vs. rural location of residence
Note: For surveys with a data set available the difference in standard error was calculated as the difference in
standard error from a model where simple random sampling was assumed and a model where clustering was
taken into account, and the median of these differences is presented in the table. Note that the standard error is
calculated for the natural log of the risk ratio, and the 95% CI is the natural log of the RR ± (1.96*standard
error). To convert the limits to a non-logarithmic scale, the antilogs of these limits are taken. E.g. for Chad, the
risk ratio for IPTp for SES was 2.815 and the 95% CI 2.387-3.320; the natural logs for the limits are 0.8700 and
1.200 respectively, and the standard error can be calculated as 0.0842. The correction for clustering of 0.0190 is
added (the adjusted standard error becomes 0.1032), so the natural logs of the confidence interval change into
0.8328 and 1.2372, and when these are converted using antilogs, the 95% confidence interval changes into
2.2997 to 3.446 (or 2.30-3.45 when rounded).
eSupplem
en
t 4
: F
low di
agr
am
for
inc
lusion an
d e
xc
lusion o
f sur
ve
ys
eF
igur
e 4
: Flow
d
iagram
for in
clu
sion
and
ex
cl
u
sion
of su
rveys
for th
e revie
w
o
f cove
rage of
m
alaria p
reven
tion
in
p
regn
an
cy in
s
u
b-S
ah
aran
Afri
ca, 20
09-11
38
c
o
untrie
s I
P
Tp p
o
licy
Screening
Included
Eligibility
Identification
45
co
untri
es ITN p
o
licy fo
r
pre
gnant
wo
me
n
45
m
alari
o
u
s c
o
untrie
s in s
u
b-Saharan Africa
No
te
: Tanzania and Zanzib
ar co
nside
re
d
as
se
parat
e
c
o
untrie
s
-2
ex
cluded, l
o
w
m
alaria
ris
k, no
M
iP
po
licie
s: S
o
uth Africa
and
Cape
Ve
rde
-5
e
xclude
d, no IPTp po
lic
y:
Burundi, D
jibo
u
ti,
Eritre
a,
Ethio
p
ia and S
w
aziland
-2
e
xclude
d, IPTp po
licy
withdrawn: Nam
ibia,
Rwan
da
29
n
ation
al
su
rv
eys
with
IP
Tp
dat
a in 20
09
-11
fr
om
28
co
untries
38
na
tio
n
al sur
ve
ys
with IT
N
dat
a in 20
09
-11
fr
om
37
co
untries
-9
e
xclude
d, sur
ve
y c
o
nducte
d
o
r planne
d but
n
o
dat
a ye
t
av
ailable:
Central
African
Republic, Como
ro
s, Gab
o
n,
Ghana, Guinea,
M
ali,
M
auritania, Niger,
Som
alia
-4
e
xclude
d, sur
ve
y
co
nducte
d
o
r planne
d but
no
data
ye
t available
:
Com
o
ro
s, Ghana,
Guinea,
M
auritania
-3
e
xclude
d, no surve
y
planne
d:
Botswana,
Eritr
e
a,
Sao
T
o
m
e
& P
rinci
p
e
27
natio
n
al
surve
ys
include
d
fro
m
27
c
o
unt
rie
s
-1
e
xclude
d, be
caus
e
t
w
o
national sur
ve
ys in
one
yea
r:
MI
S Mal
awi
20
10
-1
e
xclude
d, stud
y po
pulati
o
n
included pregnant w
o
men
still
takin
g IP
Tp
: M
IS Sudan 20
09
37
na
tio
n
al sur
ve
ys include
d
fro
m
37
c
o
unt
rie
s
-1
e
xclude
d, be
caus
e
t
w
o
natio
n
al sur
ve
ys in
one
yea
r:
MI
S Mal
awi
20
10
2
10
IPT
p: in
term
itten
t prev
en
ti
ve t
reat
m
ent. IT
N: in
secticide-tre
ate
d n
ets
. MiP
: m
alaria i
n preg
na
nc
y. MI
S: Malaria In
dicat
or Su
rv
ey.
Note: In
clusion
criteria: Malar
iou
s coun
tries i
n s
ub-Sah
ara
n Af
rica
w
ith
eit
he
r IPT
p or I
T
N policy
fo
r preg
na
nt
w
om
en
an
d n
atio
na
l su
rv
ey
w
ith
cov
erag
e data f
or IP
T
p, or
IT
N u
se in
th
e ti
m
e period 20
09-11. F
or
IP
Tp, th
e s
tu
dy
popu
lation
sh
ould n
ot in
cl
ud
e preg
na
nt
w
om
en
. If
m
ore th
an
on
e su
rv
ey
w
as
con
du
cte
d i
n 2
009-11,
on
ly
th
e l
as
t
sur
ve
y w
as u
se
d.
2
11
eS
u
pplem
ent 5
: Use of
m
alaria pr
evention in p
regnancy in sub-Sahara
n Af
rica as reported in national surveys, 2005-11
eTable 5.
1: Cov
erage
of in
te
rm
itten
t p
reven
tive treatm
en
t in
s
u
b
-S
ah
aran
Africa as
rep
orted
in
n
ation
al s
u
rveys
, 2005
-11
Co untr y P oli cy Ado pte d* Sur ve y i n 2 005 -08 Sur ve y i n 2 009 -11 R ef eren ce Sa m pl e si ze SP , an y, % IPT p 2 + ANC % IPT p2 + ANC vi sitor s, % ¶ R efe ren ce or ex pect ed s urv ey Sa m pl e Si ze SP , an y, % IPT p 2 + , ANC, % IPT p2 + ANC vi sitor s %¶ IPT p 2 + Any so ur ce Ang ol a IP T p2 20 05 MI CS 200 8-9 N R N R 16 .4 24 .3 MI S 20 11 30 94 30 .1 17 .5 ¦ 18 .6 Ben in IP T p2 2005 DHS 2 006 6380 4. 9 3. 0‡ ¦ D H Sp 2 011-12 5130 NYA 22 .8 26 .6 NYA Bot sw an a No I P T p Bu rk in a Fas o IP T p2 2005 MI CS 200 6 2370 1. 8 1. 3‡ ¦ DHS 2 010 -11 5988 73 .8 10 .6 11 .2 20 .8 B ur undi No I P T p C am eroon IP T p2† 2004 MI CS 200 6 2834 9. 7 5. 8 7. 9 D H Sp 2 011 4075 NYA 25 .6 30 .2 26 .7 C en tra l A fri can Re publ ic IP T p2 20 04 MI CS 200 6 40 85 12 .0 8. 7‡ ¦ MI CS 201 0 N Y A Cha d IP T p2 2004 No d ata MI CS 201 0 6217 10 .8 9. 3 21 .9 NR Co m or os IP T p2 2003 No d ata DHS 2 012 NYA C on go ( B ra zz av ille) IP T p2 2006 DHS 2 005 3568 2. 0 NR D H Sp 2 011-12 3426 NYA 22 .2 24 .0 NYA Cô te d'Ivo ir e IP T p2 20 05 MI CS 200 6 35 86 12 .0 8. 3‡ ¦ D H Sp 2 012 30 39 N Y A 17 .6 19 .4 N Y A Dji bo uti No I P T p DR Co ngo IP T p2 20 04 D H S 20 07 34 35 16 .2 5. 1 6. 0 MI CS 201 0 50 36 34 .3 18 .1 20 .7 N R Eq ua to ri al G uin ea IP T p2 2005 MI S 20 08 83 8 40 .7 21 .4 ‡ ¦ MI S 20 09 74 5 48 .7 29 .8 ‡ ¦ 29 .8 Erit re a No I P T p M IS 20 08 NYA Et hi op ia No I P T p Ga bo n IP T p2 2003 No d ata DHS 2 012 NYA Ga m bi a IP T p2 2003 MI S 20 08 97 9 99 .6 48 .9 ¦ MI CS 201 0 4963 94 .8 64 .9 66 .2 NR Gha na IP T p3 20 03 D H S 20 08 11 78 58 .2 43 .7 47 .4 MI CS 201 1 N Y A Gui ne a IP T p2 2005 DHS 2 005 4447 4. 5 2. 9 3. 5 DHS 2 012 NYA G uin ea -Bis sa u IP T p2 20 04 MI CS 200 6 25 06 10 .3 7. 4‡ ¦ MI CS p 20 10 N Y A N Y A 14 .2 15 .3 N R Ke nya IP T p2† 1999 DHS 2 008 -9 2264 35 .5 14 .0 15 .3 MI S 20 10 1509 46 .9 25 .4 29 .6 25 .7 Lib eri a IP T p2 20 04 MI S 20 08-9 15 73 57 .9 45 .1 47 .3 MI S 20 11 12 30 63 .2 49 .6 ¦ 50 .3 Ma daga sc ar IP T p2 2004 DHS 2 008 -9 4807 11 .8 6. 4 7. 4 MI S 20 11* * 2477 31 .6 19 .5 ¦ 19 .5 Ma law i IP T p2† 19 93 MI CS 200 6 10 55 2 80 .7 46 .7 ‡ ¦ D H S 20 10 77 24 87 .6 53 .8 56 .8 55 .0 Ma li IP T p2 2003 DHS 2 006 5663 16 .1 4. 0 5. 7 MI CS 200 9-10 NYA Ma ur ita nia IP T p2 20 06 N o dat a MI CS 201 1 N Y A Mo za m bi que IP T p3 2006 MI CS 200 8 5191 56 .9 43 .1 ‡ ¦ D H Sp 2 011 4193 NYA 18 .6 20 .5 NYA Na m ibi a IP T p2 20 05 -2 01 0 D H S 20 06 -7 20 54 27 .8 10 .0 10 .6 MI S 20 09* * 19 2 8. 3§ 4. 9§ ¦ Ni ge r IP T p2 2005 DHS 2 006 6301 <1 <1 ¦ DHS 2 012 NYA Ni ge ria IP T p2 20 04 D H S 20 08 11 02 7 10 .9 4. 9 8. 5 MI S 20 10 22 55 20 .2 13 .2 23 .0 17 .4 Rw an da IP T p2 2005 -20 08 DHS 2 007 -8 2267 53 .0 17 .2 18 .0 Sa o To m e & P . IP T p2 20 04 MI CS 200 6 N R D H S 20 08 -9 73 3 88 .1 59 .8 61 .0 61 .6 Se ne ga l IP T p2 2004 MI S 20 08-9 5406 78 .1 52 .2 ¦ DHS 2 010 -11 4509 68 .2 38 .6 41 .4 40 .1 Si er ra L eo ne IP T p2 20 04 D H S 20 08 24 78 19 .5 10 .3 11 .9 MI CS 201 0 34 62 53 .0 38 .5 41 .4 N R So m alia IP T p2 2002 MI CS 200 6 2325 2. 2 0. 9‡ ¦ MI CS 201 1 NYA So uth Suda n IP T p2 20 05 N o dat a MI S 20 09 99 7 21 .6 12 .7 23 .1 19 .6 Suda n IP T p2 2005 MI S 20 05 95 2 3. 6 1. 8 2. 5 MI S 20 09 1966 2. 5§ 0. 6§ ¦2
12
Co untr y P oli cy Ado pte d* Sur ve y i n 2 005 -08 Sur ve y i n 2 009 -11 Sw az il an d No I P T p Tan zan ia , m ain la nd IP T p2 2001 MI S 20 07-8 2967 58 .4 29 .6 30 .5 DHS 2 009 -10 3179 62 .7 25 .7 26 .8 26 .7 To go IP T p2 20 03 MI CS 200 6 16 27 23 .2 18 .1 ‡ ¦ MI CS 201 0 17 92 52 .4 35 .9 50 .1 N R U gan da IP T p2 2000 DHS 2 006 3247 36 .6 16 .2 17 .3 DHS 2 011 3092 48 .4 24 .5 25 .8 26 .7 Za m bi a IP T p3 20 01 MI S 20 08 23 91 80 .0 60 .3 ¦ MI S 20 10 24 35 85 .8 69 .4 ¦ 70 .2 Za nz ib ar IP T p2 2001 MI S 20 07-8 77 78 .4 51 .5 53 .8 DHS 2 009 -10 87 84 .1 47 .0 47 .0 47 .3 Zi m ba bw e IP T p3 20 04 D H S 20 05 -6 21 44 12 .1 6. 3 6. 7 D H S 20 10 -1 1 24 48 13 .9 7. 3 8. 3 7. 8
A
N
C: a
nten
atal cli
nic. DHS:
De
m
og
rap
hic an
d Healt
h S
urv
ey
. DHSp
: p
reli
m
in
ar
y re
su
lt
s
of
DHS.
IP
Tp
2: in
ter
m
itte
nt p
rev
en
ti
ve
tre
at
m
ent u
sing
2 dos
es
of
S
P
. IP
T
p3: in
term
itten
t prev
en
tiv
e
treat
m
en
t using
3 dos
es of
SP
. IPT
p 2+, A
N
C: inter
m
itten
t p
rev
en
tiv
e treat
m
ent
w
ith
at lea
st 2 doses of
SP
, of
w
hic
h at least o
ne
f
ro
m
th
e
A
N
C. MICS
: Mu
ltiple In
dicator Cl
us
ter Surv
ey
.
MIC
S
p; preli
m
in
ar
y resu
lt
s of MIC
S
. MIS
: Malaria In
dicat
or S
urv
ey
. MIS
p: preli
m
in
ar
y res
ult
s of
MIS
. NR
: Not report
ed. NYA
: s
ur
ve
y d
ata n
ot
ye
t av
ailab
le. SP
: su
lfad
ox
in
e-py
rim
eth
am
in
e.
*B
es
t esti
m
ate o
n p
olic
y ad
op
tio
n d
ate f
ro
m
a
vailab
le reso
ur
ces
8†A
lt
hough
n
o f
or
m
al
3-dos
e SP policy
h
as
bee
n adopted, an
ten
atal s
ta
ff i
n Mala
w
i an
d Ke
ny
a are en
co
ur
ag
ed to g
iv
e S
P
at ev
er
y a
nten
atal
visit
w
hich
is at least o
ne
m
on
th
ap
art f
ro
m
th
e
prev
iou
s dos
e. C
am
eroon
m
ay h
av
e s
w
itc
he
d to IP
Tp3+.
‡Any
S
P
or IP
T
p2+ f
rom
a
ny
so
ur
ce, n
ot j
us
t A
N
C
§
T
he
M
IS in N
amib
ia
u
se
d p
re
gna
nt
w
ome
n a
s sa
m
ple
a
nd
no
t w
ome
n
w
ith
a
b
irt
h in t
he
la
st 2
o
r 5
y
ea
rs a
s is t
he
us
ua
l sa
m
ple
fo
r t
he oth
er su
rv
ey
s.
T
he MIS
in
S
udan
u
sed pregnan
t w
om
en
or w
om
en
w
ith
a birth
in
th
e pas
t y
ear.
¶ IPTp w
ith
at lea
st t
w
o dos
es
of
S
P
of
w
hic
h at leas
t on
e
from
th
e
ANC
a
s percen
tag
e a
m
on
g e
sti
m
ated num
ber of
A
N
C
atten
dees
, usi
ng
th
e reported p
ercen
tag
e
A
N
C atte
nd
an
ce (at
least on
e
visi
t) in
th
e sa
m
e rep
or
t.
¦N
ot en
ou
gh
in
fo
rm
ation
a
vail
able to calcu
late cov
erag
e of
2
+ dos
es
of
SP
of
w
hic
h at leas
t on
e f
ro
m
th
e
A
N
C
a
m
on
g ANC
–atten
dee
s.
**S
ur
ve
y c
ond
uc
te
d i
n a
re
as a
t m
ala
ria
r
isk o
nl
y i
n t
he
c
ou
nt
ry
eTabl
e 5.
2:
Us
e of in
se
cticid
e-treated
n
ets
d
u
rin
g p
regn
an
cy in
s
u
b
-S
ah
aran
Africa as
rep
orted
in
n
ation
al s
u
rveys
,
2005-11
Co untr y Ado pte d* Sur ve y i n 2 005 -08 Sur ve y i n 2 009 -11 Inse cti cid e r esi du al sp ra yi ng (IRS) Re fe re nc e Sa m pl e si ze IT N, % R efe ren ce or ex pect ed s urv ey Sa m pl e Si ze IT N, % IRS a nd/o r IT N, % IR S rec om m en ded (y ea r ad op te d)9 IRS sa m pl e si ze (ho use hol ds) IRS ho use ho lds, % (sur ve y 20 09 -11 ) Ang ol a 20 00 MI CS 200 8-9 N R 18 .4 MI S 20 11 13 84 25 .6 N R Y es ( 200 3) 80 30 7. 0 Ben in 2002 DHS 2 006 1962 19 .6 D H Sp 2 011-12 1560 75 .5 NR Y es ( 200 6) No I R S re po rt ed Bot sw an a 20 06 N o dat a N o dat a Y es ( 195 0) Bu rk in a Fas o 2004 No d ata DHS 2 010 1738 44 .6 44 .9 Y es ( 200 6) 1442 4 0. 9 B ur undi 20 02 N o dat a D H S 20 10 -1 1 96 2 49 .9 49 .9 Y es ( 200 9) 85 96 0. 3 C am eroon 2003 No d ata D H Sp 2 011 78 2 19 .8 20 .8 Y es ( 200 7) 7133 2. 6 C en tra l A fri can R ep . 2006 No d ata M IC S 2 01 0 NYA No Cha d 2003 No d ata MI CS 201 0 2273 9. 9 NR Yes (NR ) No I R S re po rt ed Co m or os 2001 No d ata DHS 2 012 NYA Yes (NR ) C on go ( B ra zz av ille) 2004 DHS 2 005 66 5 4. 2 D H Sp 2 011-12 1123 20 .7 NR Yes (NR ) No I R S re po rt ed Cô te d'Ivo ir e 20 05 N o dat a D H Sp 2 011-20 12 11 21 39 .9 41 .2 N o 10 22 6 1. 4 Dji bo uti 2000 MI S 20 08-9 16 3 25 .2 MI CS 201 1 NYA Y es ( 200 6) 50 5 14 .0 DR Co ngo 20 06 D H S 20 07 11 50 7. 1 MI CS 201 0 16 13 42 .6 N R Y es ( 200 7) N o I R S r epo rte d Eq ua to ri al G uin ea 2007 MI S 20 08 52 1 50 .9 MI S 20 09 42 4 35 .3 NR Y es ( 200 5) 3162 55 .0 Erit re a 20 02 MI S 20 08 N Y A N o dat a Y es ( 199 5) Et hi op ia 2001 MI S 20 07 56 8 35 .2 MI S 20 11 ‡ 39 0 34 .7 NR Y es ( 196 0) 1044 4 29 .2 Ga bo n 2003 ONS 2 008 86 0 36 .2 DHS 2 011 NYA No Ga m bi a 2002 MI S 20 08 40 2 45 .0 MI CS 201 0 1545 26 .1 NR Y es ( 200 8) No I R S re po rt ed Gha na 19 99 D H S 20 08 35 3 19 .9 MI CS 201 1 N Y A Y es ( 200 5) Gui ne a 2002 ONS 2 007 -8 2141 3. 2 DHS 2 012 NYA No G uin ea -Bis sa u 2004 No d ata M IC Sp 2 010 NYA 31 .7 NYA Yes (2 00 6) NYA Ke nya 2001 DHS 2 008 -9 60 1 49 .0 MI S 20 10 39 8 41 .1 48 .5 Y es ( 200 3) 6538 10 .8 Lib eri a 20 04 MI S 20 08-9 47 1 32 .9 MI S 20 11 36 3 39 .0 45 .4 Y es ( 200 9) 41 62 8. 6 Ma daga sc ar 2000 DHS 2 008 -9 1425 46 .2 MI S 20 11 ‡ 65 7 71 .5 85 .6 Y es ( 199 3) 8049 40 .7 Ma law i 20 02 MI CS 200 6 10 55 2 25 .6 † D H S 20 10 20 86 35 .2 36 .2 Y es ( 200 7) 24 82 5 2. 2 Ma li 2006 DHS 2 006 1896 28 .9 MI S 20 10 2191 62 .7 † NR Y es ( 200 7) 1617 5. 1 Ma ur ita nia 2002 No d ata M IC S 2 01 1 NYA No Mo za m bi que 2003 MI S 20 07 58 9 7. 3 D H Sp 2 011 1450 19 .5 33 .5 Y es ( 200 3) 1391 9 18 .5 Na m ibi a 20 02 D H S 20 06 -7 54 1 8. 8 MI S 20 09 ‡ 19 4 25 .9 N R Y es ( 196 5) 28 23 21 .7 Ni ge r 1998 DHS 2 006 1311 6. 7 ONS 2 010 NR 71 .5 NR Y es ( 200 3) No I R S re po rt ed Ni ge ria 20 01 D H S 20 08 33 97 4. 8 MI S 20 10 75 2 33 .6 34 .0 Y es ( 200 7) 58 95 0. 7 Rw an da 2000 DHS 2 007 -8 67 3 60 .3 DHS 2 010 -11 95 2 72 .2 NR Y es ( 200 9) No I R S re po rt ed Sa o To m e & P rin cipe 20 04 D H S 20 08 -9 23 7 56 .7 N o dat a Y es ( 200 3) Se ne ga l 1998 MI S 20 08-9 2949 28 .5 DHS 2 010 -11 1279 36 .0 43 .1 Y es ( 200 5) 7902 9. 1 Si er ra L eo ne 20 00 D H S 20 08 61 5 27 .2 MI CS 201 0 14 31 26 .6 N R Y es ( 201 0) N o I R S r epo rte d So m alia 2002 FS NA U 20 08-9 1060 1 20 .9 † MI CS 201 1 NYA Y es ( 200 4) So uth Suda n 20 04 N o dat a MI S 20 09 52 4 29 .3 N R N o 25 45 2. 4 Suda n 2001 MI S 20 05 33 0 12 .7 MI S 20 09 64 3 17 .2 NR Y es ( 195 6) No I R S re po rt ed Sw az il an d 20 02 D H S 20 06 -7 29 6 0. 9 MI S 20 10 ‡ 12 96 3. 8† N R Y es ( 194 7) 17 51 44 .5 Tan zan ia , m ain la nd 2004 MI S 20 07-8 82 3 26 .0 DHS 2 009 -10 92 2 57 .1 NR Y es ( 200 6) No I R S re po rt ed To go 20 01 N o dat a MI CS 201 0 47 0 46 .3 N R Y es ( 201 1) N o I R S r epo rte d U gan da 2003 DHS 2 006 1019 10 .0 DHS 2 011 1009 46 .9 49 .8 Y es ( 200 5) 9033 7. 2 Za m bi a 20 00 MI S 20 08 41 6 43 .2 MI S 20 10 34 2 45 .9 N R Y es ( N R) 43 61 23 .1 Za nz ib ar 2004 MI S 20 07-8 23 51 .3 DHS 2 009 -10 25 49 .5 NR Y es ( 200 6) No I R S re po rt ed2
14
Zi m ba bw e 20 01 MI S 20 08 23 8 5. 6 D H S 20 10 -1 1 76 4 9. 6 23 .2 Y es ( 194 8) 97 56 17 .0
DHS: De
m
og
raph
ic a
nd Healt
h S
urv
ey
. D
H
Sp: preli
m
in
ar
y res
ult
s of
DHS. MI
C
S
: M
ultip
le In
dicator C
lu
ster Su
rv
ey
. F
S
N
A
U: Food Secu
rit
y an
d N
utrition
Unit-So
m
al
ia. IRS: In
door
R
es
id
ual Spra
yin
g. IT
N: In
sec
ticide treated n
et. MIC
S
p: preli
m
in
ar
y res
ult
s of
MIC
S
. MIS
: Malaria In
dicator Su
rv
ey
. M
ISp: prel
im
in
ar
y re
su
lts o
f MI
S. NR: No
t rep
or
ted
. NYA
: s
urv
ey
d
ata
no
t y
et a
vailab
le. ONS: Ot
he
r Natio
na
l S
urv
ey
.
*
B
est esti
m
ate o
n p
olic
y ad
op
tio
n d
ate f
or p
reg
nan
t w
om
en
as targ
et
gr
ou
p f
or IT
Ns
f
rom
av
ai
lable res
ou
rces
8†S
tu
dy
popu
la
tio
n i
s n
on-pregn
an
t w
om
en
; n
o i
nf
or
m
at
io
n for preg
na
nt
w
om
en
av
ail
abl
e i
n t
he
se su
rv
ey
s.
‡Madag
as
car: 3 n
on-m
alaria
l dis
tricts
(
A
nta
na
nariv
o R
en
ivoh
itra, An
tsirabe I, F
ian
aran
tsoa) an
d com
m
un
iti
es
> 1500
m
eter abov
e
sea lev
el ex
cl
ud
ed
f
ro
m
s
ur
ve
y; Eth
iopia: on
ly
areas
in
cl
ud
ed
w
ith
altit
ud
e <2000
m
eter. Na
m
ibia an
d S
w
azila
nd: s
urv
ey
con
du
cted i
n areas
a
t m
alaria ris
k.
2
15
eS
u
pplem
ent 6
: C
alc
ula
tions o
f n
u
m
be
r o
f bir
ths c
ov
er
ed by int
erm
itte
nt
pr
ev
ent
iv
e t
re
atm
en
t, ins
ec
tic
ide
-tr
ea
te
d ne
ts a
nd a
nt
enat
al c
ar
e in
2010,
sub-Saharan A
frica, 2009-11
eTable 6.
1: Ca
lcula
tio
n o
f nu
m
b
er o
f births pro
tected by
inter
m
ittent
prev
entiv
e trea
tm
en
t in su
b-Sa
ha
ra
n Africa
, pro
jected fo
r
20
10
Co untr y UNDP 2010 10 D ell ic ou r 2 01 05 suppl em ent 2 E sti m ate d nu m be r of liv e an d stillb irt hs Ge thi ng 2010 6 suppl em ent 1 Ma la ri a ex po sed Liv e + s till-bi rths f or 2010 Co un tr ie s wit h IPT p po li cy Co untr ie s wi th IPT p su rv ey 20 09 -1 1 Ma la ri a ex po se d bi rths i n cou nt ries wit h I P Tp po licy , 2010 Ma la ri a ex po sed bi rths f or 2010 in cou nt ries wit h I P Tp su rv ey in 20 09 -1 1 IPT p cov era ge 20 09 -11 ( 2+ do se s) % 95 % CI* , % N u m ber o f ma la ria ex po sed bi rths pr ot ec te d b y IPT p fo r 2010 Lo we r 95% C I bi rths pr ote cte d Uppe r 95% C I bi rths pr ote cte d Liv e b irt hs Liv e bi rths (% ) St illb irt hs (% ) % Po pu la tio n no t m ala ria ex po sed A ng ol a 77 4, 000 75 .1 2. 5 79 9, 766 1. 8 78 5, 370 1 1 78 5, 370 78 5, 370 17 .5 14 .6-20 .4 13 7, 440 11 4, 664 16 0, 215 Be ni n 33 6, 000 73 .9 2. 3 34 6, 45 7 0. 0 34 6, 45 7 1 1 34 6, 45 7 34 6, 45 7 22 .8 21 .0-24 .6 78 ,9 92 72 ,7 56 85 ,2 29 Bo ts w ana 47 ,0 00 68 .3 1. 3 47 ,8 95 46 .8 25 ,4 80 Bur ki na F as o 67 2, 00 0 73 .9 2. 0 69 0, 18 7 0. 0 69 0, 18 7 1 1 69 0, 18 7 69 0, 18 7 10 .6 9. 2-12 .0 73 ,1 60 63 ,4 97 82 ,8 22 Bur un di 26 8, 000 70 .4 2. 5 27 7, 517 29 .3 19 6, 205 Cam ero on 69 1, 000 75 .1 2. 1 71 0, 322 1. 8 69 7, 536 1 1 69 7, 536 69 7, 536 25 .6 23 .8-27 .4 17 8, 569 16 6, 014 19 1, 125 CA R 15 0, 000 75 .1 2. 2 15 4, 394 0. 0 15 4, 394 1 15 4, 394 Ch ad 48 2, 00 0 75 .1 2. 6 49 8, 68 7 0. 0 49 8, 68 7 1 1 49 8, 68 7 49 8, 68 7 9. 3 8. 0-10 .6 46 ,3 78 39 ,8 95 52 ,8 61 Co m or os 27 ,0 00 70 .4 1. 9 27 ,7 29 2. 8 26 ,9 52 1 26 ,9 52 Co ng o 13 6, 000 75 .1 2. 2 13 9, 98 4 0. 0 13 9, 98 4 1 1 13 9, 98 4 13 9, 98 4 22 .2 20 .2-24 .2 31 ,0 76 28 ,2 77 33 ,8 76 Co te d' Ivo ire 66 0, 000 73 .9 2. 6 68 3, 221 0. 0 68 3, 221 1 1 68 3, 221 68 3, 221 17 .6 15 .6-19 .6 12 0, 247 10 6, 582 13 3, 911 D jibo uti 25 ,0 00 70 .4 2. 5 25 ,8 88 34 .8 16 ,8 79 D R C 2, 77 2, 000 75 .1 2. 6 2, 86 7, 968 6. 2 2, 69 0, 154 1 1 2, 69 0, 154 2, 69 0, 154 18 .1 16 .5-19 .7 48 6, 918 44 3, 875 52 9, 960 Eq uato rial G uine a 24 ,0 00 75 .1 2. 0 24 ,6 39 0. 7 24 ,4 67 1 1 24 ,4 67 24 ,4 67 29 .8 25 .9-33 .7 7, 29 1 6, 33 7 8, 24 5 Er itr ea 18 3, 00 0 70 .4 2. 0 18 8, 19 9 11 .3 16 6, 93 2 E th io pia 2, 61 9, 000 70 .4 2. 6 2, 71 5, 724 36 .6 1, 72 1, 769 G abo n 39 ,0 00 75 .1 1. 4 39 ,7 27 0. 0 39 ,7 27 1 39 ,7 27 G am bia 64 ,0 00 73 .9 2. 1 65 ,8 19 0. 0 65 ,8 19 1 1 65 ,8 19 65 ,8 19 64 .9 63 .0-66 .8 42 ,7 16 41 ,4 66 43 ,9 67 G hana 75 1, 000 73 .9 1. 8 76 9, 292 0. 0 76 9, 292 1 76 9, 292 G uine a 38 0, 000 73 .9 2. 2 39 1, 313 0. 0 39 1, 313 1 39 1, 313 G uine a B iss au 57 ,0 00 73 .9 2. 7 59 ,0 83 0. 0 59 ,0 83 1 1 59 ,0 83 59 ,0 83 14 .2 12 .2-16 .2 8, 39 0 7, 20 8 9, 57 1 K eny a 1, 44 7, 000 70 .4 3. 3 1, 51 4, 828 29 .1 1, 07 4, 013 1 1 1, 07 4, 013 1, 07 4, 013 25 .4 22 .7-28 .1 27 2, 799 24 3, 801 30 1, 798 L ibe ria 14 5, 000 73 .9 2. 4 14 9, 70 9 0. 0 14 9, 70 9 1 1 14 9, 70 9 14 9, 70 9 49 .6 45 .9-53 .3 74 ,2 56 68 ,7 16 79 ,7 95 Ma dag as car 69 8, 000 70 .4 2. 1 71 8, 821 9. 7 64 9, 095 1 1 64 9, 095 64 9, 095 19 .5 16 .8-22 .2 12 6, 574 10 9, 048 14 4, 09921
6
Co untr y UNDP 2010 10 D ell ic ou r 2 01 05 suppl em ent 2 E sti m ate d nu m be r of liv e an d stillb irt hs Ge thi ng 2010 6 suppl em ent 1 Ma la ri a ex po sed Liv e + s till-bi rths f or 2010 Co un tr ie s wit h IPT p po li cy Co untr ie s wi th IPT p su rv ey 20 09 -1 1 Ma la ri a ex po se d bi rths i n cou nt ries wit h I P Tp po li cy , 2010 Ma la ri a ex po sed bi rths f or 2010 in co untr ie s wit h I P Tp su rv ey in 20 09 -1 1 IPT p cov era ge 20 09 -11 ( 2+ do se s) % 95 % CI* , % N u m ber o f ma la ria ex po se d bi rths pr ot ec te d b y IPT p fo r 2010 Lo we r 95% C I bi rths pr ote cte d Uppe r 95% C I bi rths pr ote cte d Liv e b irt hs Liv e bi rths (% ) St illb irt hs (% ) % Po pu la tio n no t m ala ria ex po sed Mal aw i 61 0, 000 70 .4 2. 9 63 5, 128 0. 0 63 5, 128 1 1 63 5, 128 63 5, 128 53 .8 52 .4-55 .2 34 1, 699 33 2, 807 35 0, 591 Mal i 68 0, 000 73 .9 1. 8 69 6, 563 0. 0 69 6, 563 1 69 6, 563 Ma ur ita nia 11 3, 000 73 .9 2. 3 11 6, 517 5. 0 11 0, 691 1 11 0, 691 Mo za m bi que 86 9, 000 70 .4 2. 3 89 7, 391 0. 1 89 6, 493 1 1 89 6, 493 89 6, 493 18 .6 16 .8-20 .4 16 6, 748 15 0, 611 18 2, 885 N am ibia 60 ,0 00 68 .3 1. 3 61 ,1 42 15 .4 51 ,7 26 N ig er 70 5, 000 73 .9 2. 9 73 2, 666 0. 0 73 2, 666 1 73 2, 666 N ig eri a 6, 02 6, 000 73 .9 2. 3 6, 21 3, 548 0. 0 6, 21 3, 548 1 1 6, 21 3, 548 6, 21 3, 548 13 .2 10 .7-15 .7 82 0, 188 66 4, 850 97 5, 527 Rw and a 40 4, 00 0 70 .4 2. 2 41 6, 62 5 43 .4 23 5, 81 0 Sa o T om e & P . 5, 00 0 75 .1 1. 9 5, 12 6 3. 6 4, 94 2 1 1 4, 94 2 4, 94 2 59 .8 55 .1-64 .5 2, 95 5 2, 72 3 3, 18 8 Se ne ga l 45 0, 000 73 .9 2. 0 46 2, 179 0. 0 46 2, 179 1 1 46 2, 179 46 2, 179 38 .6 36 .2-41 .0 17 8, 401 16 7, 309 18 9, 493 Sie rra L eo na 22 4, 00 0 73 .9 2. 8 23 2, 48 7 0. 0 23 2, 48 7 1 1 23 2, 48 7 23 2, 48 7 38 .5 36 .3-40 .7 89 ,5 08 84 ,3 93 94 ,6 22 So m alia 39 1, 000 70 .4 3. 3 40 9, 328 0. 0 40 9, 205 1 40 9, 205 Sud an ( N or th) 1, 38 4, 981 69 .9 3. 9 1, 46 2, 254 0. 0 1, 46 2, 108 1 1, 46 2, 108 Su da n ( So uth ) 26 8, 69 0 69 .9 3. 9 28 3, 68 1 0. 0 28 3, 65 3 1 1 28 3, 65 3 28 3, 65 3 12 .7 10 .0-15 .4 36 ,0 24 28 ,3 65 43 ,6 83 Sw az iland 34 ,0 00 68 .3 1. 5 34 ,7 47 77 .1 7, 95 7 T anz ani a Ma inl . 1, 74 1, 000 70 .4 2. 1 1, 79 2, 933 3. 8 1, 72 4, 802 1 1 1, 72 4, 802 1, 72 4, 802 25 .7 23 .5-27 .9 44 3, 274 40 5, 328 48 1, 220 T ogo 19 0, 00 0 73 .9 2. 0 19 5, 14 2 0. 0 19 5, 14 2 1 1 19 5, 14 2 19 5, 14 2 35 .9 33 .2-38 .6 70 ,0 56 64 ,7 87 75 ,3 25 U gand a 1, 43 3, 000 70 .4 2. 3 1, 47 9, 817 6. 5 1, 38 3, 629 1 1 1, 38 3, 629 1, 38 3, 629 24 .5 22 .7-26 .3 33 8, 989 31 4, 084 36 3, 894 Z am bia 54 7, 000 70 .4 2. 2 56 4, 094 0. 0 56 4, 094 1 1 56 4, 094 56 4, 094 69 .4 67 .0-71 .8 39 1, 481 37 7, 943 40 5, 019 Z anz ibar 50 ,4 89 70 .4 2. 1 51 ,9 95 0. 0 51 ,9 95 1 1 51 ,9 95 51 ,9 95 47 .0 35 .6-58 .4 24 ,4 38 18 ,5 10 30 ,3 65 Z im ba bw e 37 0, 000 70 .4 1. 6 37 8, 409 44 .5 21 0, 017 1 1 21 0, 017 21 0, 017 7. 3 5. 9-8. 7 15 ,3 31 12 ,3 91 18 ,2 71 Tot als 28 ,6 27 ,5 59 37 27 26 ,2 04 ,8 01 21 ,4 11 ,8 90 21 .5 19 .3-23 .7 4, 60 3, 89 8 4, 13 6, 23 7 5, 07 1, 55 8
