Selected article for: "accessibility testing and testing center"

Author: Christian Alvin H Buhat; Jessa Camille C Duero; Edd Francis O Felix; Jomar Fajardo Rabajante; Jonathan B Mamplata
Title: Optimal Allocation of COVID-19 Test Kits Among Accredited Testing Centers in the Philippines
  • Document date: 2020_4_17
  • ID: 1b3pigtl_12
    Snippet: where lat i and lon i are the GPS location of community i, and lat j and lon j are are the GPS location of testing center j, all in radians measure. Using d i j , we then compute for the "effective demand" f (d i j )I i or the number of infected individuals in community i that will go to testing center j for testing. We define f as a function that puts 'weight' on the testing accessibility of an individual to a testing center based on the distanc.....
    Document: where lat i and lon i are the GPS location of community i, and lat j and lon j are are the GPS location of testing center j, all in radians measure. Using d i j , we then compute for the "effective demand" f (d i j )I i or the number of infected individuals in community i that will go to testing center j for testing. We define f as a function that puts 'weight' on the testing accessibility of an individual to a testing center based on the distance d i j . To model the testing accessibility, we use a Gaussian model which is used to describe the distribution of the COVID-19 infections [15] . We have f (d) = e −kd 2 , where k is a dispersal length scale parameter that can provide further information about outbreak dynamics and potential for superspreading events [11] . We use Elliot's estimation in solving for k which considers the mean µ, variance σ 2 of the distribution, and the sample size N for number of communities involved [7] :

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