An exact approach to calibrating infectious disease models to surveillance data: The case of HIV and HSV-2
When mathematical models of infectious diseases are used to inform health policy, an important first step is often to calibrate a model to disease surveillance data for a specific setting (or multiple settings). It is increasingly common to also perform sensitivity analyses to demonstrate the robust...
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AIMS Press
2018-01-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2018007 |
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| author | David J. Gerberry |
| author_facet | David J. Gerberry |
| author_sort | David J. Gerberry |
| collection | DOAJ |
| description | When mathematical models of infectious diseases are used to inform health policy, an important first step is often to calibrate a model to disease surveillance data for a specific setting (or multiple settings). It is increasingly common to also perform sensitivity analyses to demonstrate the robustness, or lack thereof, of the modeling results. Doing so requires the modeler to find multiple parameter sets for which the model produces behavior that is consistent with the surveillance data. While frequently overlooked, the calibration process is nontrivial at best and can be inefficient, poorly communicated and a major hurdle to the overall reproducibility of modeling results.In this work, we describe a general approach to calibrating infectious disease models to surveillance data. The technique is able to match surveillance data to high accuracy in a very efficient manner as it is based on the Newton-Raphson method for solving nonlinear systems. To demonstrate its robustness, we use the calibration technique on multiple models for the interacting dynamics of HIV and HSV-2. |
| format | Article |
| id | doaj-art-c634a83930c74ad7a9bf4fad28b4c934 |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-c634a83930c74ad7a9bf4fad28b4c9342025-01-24T02:40:37ZengAIMS PressMathematical Biosciences and Engineering1551-00182018-01-0115115317910.3934/mbe.2018007An exact approach to calibrating infectious disease models to surveillance data: The case of HIV and HSV-2David J. Gerberry0Department of Mathematics, Xavier University, 3800 Victory Parkway, Cincinnati, OH 45207, USAWhen mathematical models of infectious diseases are used to inform health policy, an important first step is often to calibrate a model to disease surveillance data for a specific setting (or multiple settings). It is increasingly common to also perform sensitivity analyses to demonstrate the robustness, or lack thereof, of the modeling results. Doing so requires the modeler to find multiple parameter sets for which the model produces behavior that is consistent with the surveillance data. While frequently overlooked, the calibration process is nontrivial at best and can be inefficient, poorly communicated and a major hurdle to the overall reproducibility of modeling results.In this work, we describe a general approach to calibrating infectious disease models to surveillance data. The technique is able to match surveillance data to high accuracy in a very efficient manner as it is based on the Newton-Raphson method for solving nonlinear systems. To demonstrate its robustness, we use the calibration technique on multiple models for the interacting dynamics of HIV and HSV-2.https://www.aimspress.com/article/doi/10.3934/mbe.2018007mathematical modelingcalibrationmodel-fittinghivhsv-2surveillance data |
| spellingShingle | David J. Gerberry An exact approach to calibrating infectious disease models to surveillance data: The case of HIV and HSV-2 Mathematical Biosciences and Engineering mathematical modeling calibration model-fitting hiv hsv-2 surveillance data |
| title | An exact approach to calibrating infectious disease models to surveillance data: The case of HIV and HSV-2 |
| title_full | An exact approach to calibrating infectious disease models to surveillance data: The case of HIV and HSV-2 |
| title_fullStr | An exact approach to calibrating infectious disease models to surveillance data: The case of HIV and HSV-2 |
| title_full_unstemmed | An exact approach to calibrating infectious disease models to surveillance data: The case of HIV and HSV-2 |
| title_short | An exact approach to calibrating infectious disease models to surveillance data: The case of HIV and HSV-2 |
| title_sort | exact approach to calibrating infectious disease models to surveillance data the case of hiv and hsv 2 |
| topic | mathematical modeling calibration model-fitting hiv hsv-2 surveillance data |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2018007 |
| work_keys_str_mv | AT davidjgerberry anexactapproachtocalibratinginfectiousdiseasemodelstosurveillancedatathecaseofhivandhsv2 AT davidjgerberry exactapproachtocalibratinginfectiousdiseasemodelstosurveillancedatathecaseofhivandhsv2 |