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Business Investing in Malaria Control: Economic Returns and ... - Path

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Figure A.5 illustrates the malaria episodes averted by each company.<br />

Figure A.5<br />

Estimated malaria episodes averted for Mopani Copper M<strong>in</strong>es, Konkola Copper M<strong>in</strong>es <strong>and</strong> Zambia Sugar<br />

<strong>Malaria</strong> episodes<br />

(thous<strong>and</strong>s)<br />

<br />

<br />

<strong>Malaria</strong> episodes<br />

(thous<strong>and</strong>s)<br />

<br />

<br />

12<br />

Basel<strong>in</strong>e<br />

12<br />

Basel<strong>in</strong>e<br />

9<br />

6<br />

Effect of private<br />

<strong>in</strong>terventions<br />

9<br />

6<br />

3<br />

Actual<br />

3<br />

Actual<br />

0<br />

0<br />

2001 2002 2003 2004 2005 2006 2007 2008 2009<br />

2001 2002 2003 2004 2005 2006 2007 2008 2009<br />

<strong>Malaria</strong> episodes<br />

(thous<strong>and</strong>s)<br />

<br />

BUSINESS INVESTING IN MALARIA CONTROL: ECONOMIC RETURNS AND A HEALTHY WORKFORCE FOR AFRICA<br />

Sources: Health Management Information Systems, Central Statistics Office, Zambia; company data.<br />

Company cl<strong>in</strong>ics recorded greater reductions<br />

<strong>in</strong> malaria cases than public-sector cl<strong>in</strong>ics. That<br />

is, actual malaria cases fell at higher rates than<br />

basel<strong>in</strong>e malaria cases. This difference is less<br />

dramatic <strong>in</strong> Mazabuka District (Zambia Sugar)<br />

where much of the population is affiliated with the<br />

company <strong>and</strong> the company-based control effort<br />

affected a higher proportion of the population<br />

overall.<br />

Step II: Medical cost sav<strong>in</strong>gs<br />

In order to calculate health-care cost sav<strong>in</strong>gs<br />

associated with malaria prevention, averted<br />

12<br />

9<br />

6<br />

3<br />

0<br />

Actual<br />

Basel<strong>in</strong>e<br />

2001 2002 2003 2004 2005 2006 2007 2008 2009<br />

malaria episodes were divided <strong>in</strong>to <strong>in</strong>-patient <strong>and</strong><br />

out-patient cases. It was assumed that the ratio<br />

of <strong>in</strong>-patients to out-patients was not affected by<br />

private-sector <strong>in</strong>terventions.<br />

Separate data on <strong>in</strong>-patients <strong>and</strong> out-patients<br />

were not available at Zambia Sugar. It therefore<br />

was assumed that no <strong>in</strong>-patients were admitted<br />

at Zambia Sugar. That is, all malaria episodes<br />

were considered to be (less challeng<strong>in</strong>g <strong>and</strong> less<br />

expensive) out-patient cases. Us<strong>in</strong>g the basel<strong>in</strong>es<br />

from Step I, the <strong>in</strong>-patient <strong>and</strong> out-patient trends<br />

displayed <strong>in</strong> Figure A.6 were derived.<br />

50

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