Analysis of Haematological Parameters as Predictors of Malaria Infection Using a Logistic Regression Model: A Case Study of a Hospital in the Ashanti Region of Ghana

<table class="fixed-width table-group" id="tab4"><tr><td><table class="table"><colgroup><col style="width:9.33em"/><col style="width:7.41em"/><col style="width:7.96em"/><col style="width:5.74em"/></colgroup><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td class="align_left" rowspan="2">Observed</td><td class="align_center" colspan="3"> Predicted</td></tr><tr class="thead"><td class="align_center">With malaria <svg height="11.5564pt" id="M31" style="vertical-align:-2.26807pt" version="1.1" viewbox="-0.0498162 -9.28833 15.3928 11.5564" width="15.3928pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M300 -147C201 -63 143 98 143 270S200 602 300 686L282 710C136 610 70 450 70 271V270C70 89 136 -72 282 -170L300 -147Z"></path></g><g transform="matrix(.013,0,0,-0.013,4.498,0)"><path d="M384 0V27C293 34 287 42 287 114V635C232 613 172 594 109 583V559L157 557C201 555 205 550 205 499V114C205 42 199 34 109 27V0H384Z"></path></g><g transform="matrix(.013,0,0,-0.013,10.738,0)"><path d="M275 270C275 450 212 609 64 710L45 686C145 604 203 442 203 270S147 -63 45 -147L64 -170C213 -68 275 89 275 270Z"></path></g></svg></td><td class="align_center">Without malaria (0)</td><td class="align_center">Percentage <br/>correct</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td class="align_left">With malaria <svg height="11.5564pt" id="M32" style="vertical-align:-2.26807pt" version="1.1" viewbox="-0.0498162 -9.28833 15.3928 11.5564" width="15.3928pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M300 -147C201 -63 143 98 143 270S200 602 300 686L282 710C136 610 70 450 70 271V270C70 89 136 -72 282 -170L300 -147Z"></path></g><g transform="matrix(.013,0,0,-0.013,4.498,0)"><path d="M384 0V27C293 34 287 42 287 114V635C232 613 172 594 109 583V559L157 557C201 555 205 550 205 499V114C205 42 199 34 109 27V0H384Z"></path></g><g transform="matrix(.013,0,0,-0.013,10.738,0)"><path d="M275 270C275 450 212 609 64 710L45 686C145 604 203 442 203 270S147 -63 45 -147L64 -170C213 -68 275 89 275 270Z"></path></g></svg></td><td class="align_center">417</td><td class="align_center">122</td><td class="align_center">77.4</td></tr><tr><td class="align_left">Without malaria (0)</td><td class="align_center">374</td><td class="align_center">1163</td><td class="align_center">75.7</td></tr><tr><td class="align_left">Overall percentage</td><td class="align_center"> </td><td class="align_center"> </td><td class="align_center">76.1</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Classification table for the final model.</div>

Malaria Research and Treatment

tab4

Table 4

Table 4: Analysis of Haematological Parameters as Predictors of Malaria Infection Using a Logistic Regression Model: A Case Study of a Hospital in the Ashanti Region of Ghana 

Table 4 | Analysis of Haematological Parameters as Predictors of Malaria Infection Using a Logistic Regression Model: A Case Study of a Hospital in the Ashanti Region of Ghana 