MDA historical Coverage (.csv)
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District |
Region |
Year |
Coverage PSAC |
Coverage SAC |
Coverage Adults |
Reference |
|
---|---|---|---|---|---|---|---|
0 |
Blantyre |
Southern |
2015 |
0 |
0.78 |
0 |
data |
1 |
Blantyre |
Southern |
2016 |
0 |
0.85 |
0.44 |
interpolated, mean of 2015 and 2017 |
2 |
Blantyre |
Southern |
2017 |
0 |
0.92 |
0.88 |
data |
3 |
Blantyre |
Southern |
2018 |
0 |
0.87 |
0.88 |
data |
4 |
Chiradzulu |
Southern |
2015 |
0 |
0.73 |
0.02 |
data |
5 |
Chiradzulu |
Southern |
2016 |
0 |
0.8 |
0.155 |
interpolated, mean of 2015 and 2017 |
6 |
Chiradzulu |
Southern |
2017 |
0 |
0.87 |
0.29 |
value over 100% in the data for SAC so instead we use 2018 value |
7 |
Chiradzulu |
Southern |
2018 |
0 |
0.87 |
0.9 |
data |
8 |
Mulanje |
Southern |
2015 |
0 |
0.48 |
0.96 |
data |
9 |
Mulanje |
Southern |
2016 |
0 |
0.605 |
0.96 |
interpolated, mean of 2015 and 2017 |
10 |
Mulanje |
Southern |
2017 |
0 |
0.73 |
0.96 |
values over 100% in the data so instead we used values from 2018 |
11 |
Mulanje |
Southern |
2018 |
0 |
0.73 |
0.96 |
value over 100% in the data for Adults so instead we use value for 2015 |
12 |
Nkhotakota |
Central |
2015 |
0 |
0.5 |
0.01 |
value over 100% in the data for SAC so instead we used 0.5 |
13 |
Nkhotakota |
Central |
2016 |
0 |
0.675 |
0.22 |
interpolated, mean of 2015 and 2017 |
14 |
Nkhotakota |
Central |
2017 |
0 |
0.85 |
0.43 |
value over 100% in the data for SAC so instead we used 2018 value |
15 |
Nkhotakota |
Central |
2018 |
0 |
0.85 |
0.89 |
data |
16 |
Nsanje |
Southern |
2015 |
0 |
0.75 |
0 |
data |
17 |
Nsanje |
Southern |
2016 |
0 |
0.795 |
0.41 |
interpolated, mean of 2015 and 2017 |
18 |
Nsanje |
Southern |
2017 |
0 |
0.84 |
0.82 |
data |
19 |
Nsanje |
Southern |
2018 |
0 |
0.9 |
0.88 |
data |
20 |
Phalombe |
Southern |
2015 |
0 |
0.92 |
0.04 |
data |
21 |
Phalombe |
Southern |
2016 |
0 |
0.88 |
0.445 |
interpolated, mean of 2015 and 2017 |
22 |
Phalombe |
Southern |
2017 |
0 |
0.84 |
0.85 |
data |
23 |
Phalombe |
Southern |
2018 |
0 |
0.86 |
0.92 |
data |
24 |
Balaka |
Southern |
2015 |
0 |
0.43 |
0 |
data |
25 |
Balaka |
Southern |
2016 |
0 |
0.65 |
0.44 |
interpolated, mean of 2015 and 2017 |
26 |
Balaka |
Southern |
2017 |
0 |
0.87 |
0.88 |
data |
27 |
Balaka |
Southern |
2018 |
0 |
0.83 |
0.89 |
data |
28 |
Blantyre City |
Southern |
2015 |
0 |
0.78 |
0 |
data |
29 |
Blantyre City |
Southern |
2016 |
0 |
0.85 |
0.44 |
interpolated, mean of 2015 and 2017 |
30 |
Blantyre City |
Southern |
2017 |
0 |
0.92 |
0.88 |
data |
31 |
Blantyre City |
Southern |
2018 |
0 |
0.87 |
0.88 |
data |
32 |
Chikwawa |
Southern |
2015 |
0 |
0.65 |
0 |
data |
33 |
Chikwawa |
Southern |
2016 |
0 |
0.765 |
0.49 |
interpolated, mean of 2015 and 2017 |
34 |
Chikwawa |
Southern |
2017 |
0 |
0.88 |
0.98 |
data |
35 |
Chikwawa |
Southern |
2018 |
0 |
0.74 |
0.52 |
data |
36 |
Chitipa |
Northern |
2015 |
0 |
0.62 |
0 |
data |
37 |
Chitipa |
Northern |
2016 |
0 |
0.74 |
0.345 |
interpolated, mean of 2015 and 2017 |
38 |
Chitipa |
Northern |
2017 |
0 |
0.86 |
0.69 |
errors in the data so instead we use2018 data |
39 |
Chitipa |
Northern |
2018 |
0 |
0.86 |
0.69 |
data |
40 |
Dedza |
Central |
2015 |
0 |
0.72 |
0 |
data |
41 |
Dedza |
Central |
2016 |
0 |
0.81 |
0.445 |
interpolated, mean of 2015 and 2017 |
42 |
Dedza |
Central |
2017 |
0 |
0.9 |
0.89 |
data |
43 |
Dedza |
Central |
2018 |
0 |
0.95 |
0.95 |
data |
44 |
Dowa |
Central |
2015 |
0 |
0.85 |
0.02 |
data |
45 |
Dowa |
Central |
2016 |
0 |
0.85 |
0.435 |
interpolated, mean of 2015 and 2017 |
46 |
Dowa |
Central |
2017 |
0 |
0.85 |
0.85 |
data |
47 |
Dowa |
Central |
2018 |
0 |
0.8 |
0.77 |
data |
48 |
Karonga |
Northern |
2015 |
0 |
0.97 |
0 |
data |
49 |
Karonga |
Northern |
2016 |
0 |
0.91 |
0.435 |
interpolated, mean of 2015 and 2017 |
50 |
Karonga |
Northern |
2017 |
0 |
0.85 |
0.87 |
data |
51 |
Karonga |
Northern |
2018 |
0 |
0.89 |
0.84 |
data |
52 |
Kasungu |
Central |
2015 |
0 |
0.89 |
0 |
data |
53 |
Kasungu |
Central |
2016 |
0 |
0.88 |
0.35 |
interpolated, mean of 2015 and 2017 |
54 |
Kasungu |
Central |
2017 |
0 |
0.87 |
0.7 |
data |
55 |
Kasungu |
Central |
2018 |
0 |
0.82 |
0.86 |
data |
56 |
Likoma |
Northern |
2015 |
0 |
0.52 |
0.26 |
data |
57 |
Likoma |
Northern |
2016 |
0 |
0.685 |
0.615 |
interpolated, mean of 2015 and 2017 |
58 |
Likoma |
Northern |
2017 |
0 |
0.85 |
0.97 |
no data so we used Lilongwe data for 2017 and 2018 |
59 |
Likoma |
Northern |
2018 |
0 |
0.83 |
0.9 |
no data, random |
60 |
Lilongwe |
Central |
2015 |
0 |
0.88 |
0.04 |
data |
61 |
Lilongwe |
Central |
2016 |
0 |
0.865 |
0.505 |
interpolated, mean of 2015 and 2017 |
62 |
Lilongwe |
Central |
2017 |
0 |
0.85 |
0.97 |
data |
63 |
Lilongwe |
Central |
2018 |
0 |
0.83 |
0.9 |
data |
64 |
Lilongwe City |
Central |
2015 |
0 |
0.88 |
0.04 |
data |
65 |
Lilongwe City |
Central |
2016 |
0 |
0.865 |
0.505 |
interpolated, mean of 2015 and 2017 |
66 |
Lilongwe City |
Central |
2017 |
0 |
0.85 |
0.97 |
data |
67 |
Lilongwe City |
Central |
2018 |
0 |
0.83 |
0.9 |
data |
68 |
Machinga |
Southern |
2015 |
0 |
0.45 |
0 |
data |
69 |
Machinga |
Southern |
2016 |
0 |
0.68 |
0.46 |
interpolated, mean of 2015 and 2017 |
70 |
Machinga |
Southern |
2017 |
0 |
0.91 |
0.92 |
data |
71 |
Machinga |
Southern |
2018 |
0 |
0.93 |
0.97 |
data |
72 |
Mangochi |
Southern |
2015 |
0 |
0.82 |
0.01 |
data |
73 |
Mangochi |
Southern |
2016 |
0 |
0.85 |
0.49 |
interpolated, mean of 2015 and 2017 |
74 |
Mangochi |
Southern |
2017 |
0 |
0.88 |
0.97 |
data |
75 |
Mangochi |
Southern |
2018 |
0 |
0.73 |
0.75 |
data |
76 |
Mchinji |
Central |
2015 |
0 |
0.77 |
0 |
data |
77 |
Mchinji |
Central |
2016 |
0 |
0.815 |
0.435 |
interpolated, mean of 2015 and 2017 |
78 |
Mchinji |
Central |
2017 |
0 |
0.86 |
0.87 |
data |
79 |
Mchinji |
Central |
2018 |
0 |
0.83 |
0.82 |
data |
80 |
Mwanza |
Southern |
2015 |
0 |
0.5 |
0 |
errors in the data for SAC so instead we used 0.5 |
81 |
Mwanza |
Southern |
2016 |
0 |
0.675 |
0.415 |
interpolated, mean of 2015 and 2017 |
82 |
Mwanza |
Southern |
2017 |
0 |
0.85 |
0.83 |
data |
83 |
Mwanza |
Southern |
2018 |
0 |
0.75 |
0.72 |
data |
84 |
Mzimba |
Northern |
2015 |
0 |
0.41 |
0.03 |
data for Mzimba South |
85 |
Mzimba |
Northern |
2016 |
0 |
0.7 |
0.48 |
interpolated, mean of 2015 and 2017 |
86 |
Mzimba |
Northern |
2017 |
0 |
0.99 |
0.93 |
value over 100% in the data for Adults so instead we used value for 2018 |
87 |
Mzimba |
Northern |
2018 |
0 |
0.78 |
0.93 |
data for Mzimba South |
88 |
Mzuzu City |
Northern |
2015 |
0 |
0.83 |
0 |
no data, so copied from another Northern with data, Rumphi |
89 |
Mzuzu City |
Northern |
2016 |
0 |
0.855 |
0.435 |
no data, so copied from another Northern with data, Rumphi |
90 |
Mzuzu City |
Northern |
2017 |
0 |
0.88 |
0.87 |
no data, so copied from another Northern with data, Rumphi |
91 |
Mzuzu City |
Northern |
2018 |
0 |
0.92 |
0.89 |
no data, so copied from another Northern with data, Rumphi |
92 |
Neno |
Southern |
2015 |
0 |
0.8 |
0 |
data |
93 |
Neno |
Southern |
2016 |
0 |
0.82 |
0.395 |
interpolated, mean of 2015 and 2017 |
94 |
Neno |
Southern |
2017 |
0 |
0.84 |
0.79 |
data |
95 |
Neno |
Southern |
2018 |
0 |
0.87 |
0.87 |
data |
96 |
Nkhata Bay |
Northern |
2015 |
0 |
0.5 |
0.76 |
value over 100% in the data for SAC so instead we used 0.5 |
97 |
Nkhata Bay |
Northern |
2016 |
0 |
0.66 |
0.765 |
interpolated, mean of 2015 and 2017 |
98 |
Nkhata Bay |
Northern |
2017 |
0 |
0.82 |
0.77 |
data |
99 |
Nkhata Bay |
Northern |
2018 |
0 |
0.81 |
0.8 |
data |
100 |
Ntcheu |
Central |
2015 |
0 |
0.91 |
0 |
data |
101 |
Ntcheu |
Central |
2016 |
0 |
0.865 |
0.415 |
interpolated, mean of 2015 and 2017 |
102 |
Ntcheu |
Central |
2017 |
0 |
0.82 |
0.83 |
data |
103 |
Ntcheu |
Central |
2018 |
0 |
0.84 |
0.87 |
data |
104 |
Ntchisi |
Central |
2015 |
0 |
0.5 |
0 |
value over 100% in the data for SAC so instead we used 0.5 |
105 |
Ntchisi |
Central |
2016 |
0 |
0.66 |
0.45 |
interpolated, mean of 2015 and 2017 |
106 |
Ntchisi |
Central |
2017 |
0 |
0.82 |
0.9 |
data |
107 |
Ntchisi |
Central |
2018 |
0 |
0.87 |
0.83 |
data |
108 |
Rumphi |
Northern |
2015 |
0 |
0.83 |
0 |
data |
109 |
Rumphi |
Northern |
2016 |
0 |
0.855 |
0.435 |
interpolated, mean of 2015 and 2017 |
110 |
Rumphi |
Northern |
2017 |
0 |
0.88 |
0.87 |
data |
111 |
Rumphi |
Northern |
2018 |
0 |
0.92 |
0.89 |
data |
112 |
Salima |
Central |
2015 |
0 |
0.5 |
0.33 |
value over 100% in the data for SAC so instead we used 0.5 |
113 |
Salima |
Central |
2016 |
0 |
0.675 |
0.6 |
interpolated, mean of 2015 and 2017 |
114 |
Salima |
Central |
2017 |
0 |
0.85 |
0.87 |
data |
115 |
Salima |
Central |
2018 |
0 |
0.85 |
0.78 |
value over 100% in the data for SAC so instead we used 2017 value |
116 |
Thyolo |
Southern |
2015 |
0 |
0.63 |
0.04 |
data |
117 |
Thyolo |
Southern |
2016 |
0 |
0.745 |
0.395 |
interpolated, mean of 2015 and 2017 |
118 |
Thyolo |
Southern |
2017 |
0 |
0.86 |
0.75 |
data |
119 |
Thyolo |
Southern |
2018 |
0 |
0.88 |
0.85 |
data |
120 |
Zomba |
Southern |
2015 |
0 |
0.71 |
0 |
data |
121 |
Zomba |
Southern |
2016 |
0 |
0.81 |
0.39 |
interpolated, mean of 2015 and 2017 |
122 |
Zomba |
Southern |
2017 |
0 |
0.91 |
0.78 |
data |
123 |
Zomba |
Southern |
2018 |
0 |
0.91 |
0.87 |
data |
124 |
Zomba City |
Southern |
2015 |
0 |
0.71 |
0 |
data |
125 |
Zomba City |
Southern |
2016 |
0 |
0.81 |
0.39 |
interpolated, mean of 2015 and 2017 |
126 |
Zomba City |
Southern |
2017 |
0 |
0.91 |
0.78 |
data |
127 |
Zomba City |
Southern |
2018 |
0 |
0.91 |
0.87 |
data |