Skip to main content

Table 4 Estimated annual reduction in severe malaria admissions among all-ages and among children under five years that could have been achieved with increases in malaria service point density to either 1 per 1,000 population or 1 per 750 population in the final 12 months of the study period (June 2019 to May 2020)*

From: Effectiveness of community case management of malaria on severe malaria and inpatient malaria deaths in Zambia: a dose–response study using routine health information system data

Province

# Districts with existing CCM scale-up (%)

Mean (min, max) population per malaria service point in a district, June 2019 to May 2020

# Additional CHWs required to reach 1 malaria service point per 1000

# Additional CHWs required to reach 1 malaria service point per 750

All-age severe malaria admissions, June 2019 to May 2020

U5 severe malaria admissions, June 2019 to May 2020

Observed (model prediction)

Estimated reduction with 1 malaria service point per 1000

Estimated reduction with 1 malaria service point per 750

Observed (model prediction)

Estimated reduction with 1 malaria service point per 1000

Estimated reduction with 1 malaria service point per 750

Copperbelt

4 (40%)

4903 (601, 9245)

1523

2207

10,510 (11,784)

10.8%

14.7%

3340 (3313)

12.9%

17.5%

Eastern

4 (30%)

3244 (458, 6736)

726

1025

6844 (5960)

8.3%

11.3%

3743 (3291)

10.4%

14.1%

Luapula

1 (8%)

5719 (588, 12,721)

916

1290

14,503 (16,340)

10.5%

14.2%

9112 (12,369)

10.7%

14.3%

Muchinga

3 (33%)

6400 (1173, 11,249)

684

1036

6205 (7074)

12.8%

17.9%

3015 (3499)

15.0%

20.9%

Northern

2 (17%)

6700 (814, 9576)

1228

1736

8875 (9243)

13.0%

17.6%

4480 (4595)

15.2%

20.5%

North Western

7 (64%)

2648 (431, 7976)

561

903

9702 (10,457)

10.1%

14.7%

4174 (4319)

11.5%

16.6%

Western

14 (88%)

1238 (461, 5025)

270

462

2679 (2686)

2.0%

3.3%

1048 (1069)

2.1%

3.6%

  1. *Estimated % reductions in severe malaria admissions were produced by comparing the model prediction during June 2019 to May 2020 (using the observed district-month service point density) against model predictions for the two counterfactual scenarios of all districts achieving 1 malaria service point per 1000 population or 1 malaria service point per 750 people