| Literature DB >> 34591842 |
Nantasit Luangasanatip1, Panarasri Khonputsa1, Céline Caillet2,3,4, Serena Vickers2,3,4, Stephen Zambrzycki5, Facundo M Fernández5, Paul N Newton2,3,4, Yoel Lubell1,3.
Abstract
Substandard and falsified (SF) antimalarials have devastating consequences including increased morbidity, mortality and economic losses. Portable medicine quality screening devices are increasingly available, but whether their use for the detection of SF antimalarials is cost-effective is not known. We evaluated the cost-effectiveness of introducing such devices in post-market surveillance in pharmacies in Laos, conservatively focusing on their outcome in detecting SF artemisinin-based combination therapies (ACTs). We simulated the deployment of six portable screening devices: two handheld near-infrared [MicroPHAZIR RX, NIR-S-G1], two handheld Raman [Progeny, TruScan RM]; one portable mid-infrared [4500a FTIR] spectrometers, and single-use disposable paper analytical devices [PADs]. We considered two scenarios with high and low levels of SF ACTs. Different sampling strategies in which medicine inspectors would test 1, 2, or 3 sample(s) of each brand of ACT were evaluated. Costs of inspection including device procurement, inspector time, reagents, reference testing, and replacement with genuine ACTs were estimated. Outcomes were measured as disability adjusted life years (DALYs) and incremental cost-effectiveness ratios were estimated for each device compared with a baseline of visual inspections alone. In the scenario with high levels of SF ACTs, all devices were cost-effective with a 1-sample strategy. In the scenario of low levels of SF ACTs, only four devices (MicroPHAZIR RX, 4500a FTIR, NIR-S-G1, and PADs) were cost-effective with a 1-sample strategy. In the multi-way comparative analysis, in both scenarios the NIR-S-G1 testing 2 samples was the most cost-effective option. Routine inspection of ACT quality using portable screening devices is likely to be cost-effective in the Laos context. This work should encourage policy-makers or regulators to further investigate investment in portable screening devices to detect SF medicines and reduce their associated undesired health and economic burdens.Entities:
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Year: 2021 PMID: 34591842 PMCID: PMC8483304 DOI: 10.1371/journal.pntd.0009539
Source DB: PubMed Journal: PLoS Negl Trop Dis ISSN: 1935-2727
Fig 1Decision analytic model for drug sampling at pharmacy (A Medicines Model) and malarial illness (B Patients Model).
Probability with which each device will identify genuine, substandard (between 50% and 80% API) and falsified (wrong/0% API) medicines with strategies of 1/2/3 samples per brand of ACTs.
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| Genuine | 0 | 1 | 0 | 1 | 0 | 1 | |
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| Substandard | 0.42 | 0.58 | 0.66 | 0.34 | 0.80 | 0.20 |
| Falsified | 1 | 0 | 1 | 0 | 1 | 0 | |
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| Genuine | 0 | 1 | 0 | 1 | 0 | 1 |
| Substandard | 0.5 | 0.5 | 0.75 | 0.25 | 0.88 | 0.13 | |
| Falsified | 1 | 0 | 1 | 0 | 1 | 0 | |
| Genuine | 0 | 1 | 0 | 1 | 0 | 1 | |
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| Substandard | 0.33 | 0.67 | 0.56 | 0.44 | 0.70 | 0.30 |
| Falsified | 1 | 0 | 1 | 0 | 1 | 0 | |
| Genuine | 0 | 1 | 0 | 1 | 0 | 1 | |
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| Substandard | 0.08 | 0.92 | 0.16 | 0.84 | 0.23 | 0.77 |
| Falsified | 1 | 0 | 1 | 0 | 1 | 0 | |
| Genuine | 0 | 1 | 0 | 1 | 0 | 1 | |
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| Substandard | 0.33 | 0.67 | 0.56 | 0.44 | 0.70 | 0.30 |
| Falsified | 0.95 | 0.05 | 1 | 0 | 1 | 0 | |
| Genuine | 0 | 1 | 0 | 1 | 0 | 1 | |
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| Substandard | 0 | 1 | 0 | 1 | 0 | 1 |
| Falsified | 1 | 0 | 1 | 0 | 1 | 0 | |
*Genuine medicine (90–110% API), Substandard (50% and 80% API) and Falsified medicine (wrong/0% API)
**The probability of detecting SF medicine under 2- and 3-sample strategies are estimated with each repeat sample test having the same probability as a single sample test independently.
Device:Fail refers to the probability that the device indicates that the medicine is substandard or falsified.
Device:Pass refers to the probability that the device indicates that the medicine is genuine.
List of parameters used in the cost-effectiveness analysis model.
| Parameters | Values | Reference |
|---|---|---|
| Total malaria cases per year (Lao PDR, year 2015) | 36,056 | [ |
| Number of districts where malaria cases were reported | 42 | |
| Number of pharmacies inspected per district | 10 | Laos Food and Drug Department (FDD) |
| Number of ACT brands per pharmacy | 3 | Assumed |
| Total number of malaria cases, per pharmacy per year | 86 | [ |
| Total ACT (blisters) stock of all brands, per pharmacy | 258 | Assumed |
| Number of samples tested per brand | 1–3 | Assumed |
| Number of inspections, per pharmacy per year | 2 | Lao FDD |
| Number of months genuine replacement ACTs in place until returning to baseline levels | 1 | Assumed |
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| Number of inspectors, per visit (five inspectors per district to perform inspections at 10 pharmacies) | 5 | Laos FDD |
| Hours per inspection, per pharmacy | 1 | Assumed |
| Number of pharmacy visit, per day | 2 | Assumed |
| Inspector’s salary per hour (US$ 144 or 1.2 million LAK per month) | 0.9 | Bureau of Food and Drug Inspection (BFDI), Lao PDR |
| Per diem (per day) (250,000 LAK) | 30 | Bureau of Food and Drug Inspection (BFDI), Lao PDR |
| Cost of device (up front and subsequent costs over 5 years) | See | [ |
| Cost of test, per sample (consumable material and reagents) | See | [ |
| Cost of reference analysis with HPLC (1,245 million LAK), per sample | US$ 149.4 | Bureau of Food and Drug Inspection (BFDI), Lao PDR |
| Cost of ACT, per tablet | US$ 0.78 | [ |
| Years of life with disability (YLD) due to severe malaria | 0.02 | Disability weight of 0.133 [ |
| Years of life lost (YLL) | 20 | Assumed based on life expectancy in Laos [ |
| Willingness to pay (GDP per Capita) threshold (Lao) | US$ 2,353 | [ |
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| Risk of severe malaria when treated with genuine ACT | 0 | [ |
| Risk of severe malaria when treated with substandard and falsified ACT | 0.24 | [ |
| Risk of death in severe malaria | 0.15 | [ |
| Risk of death in non-severe malaria | 0 | [ |
*MRA–Medicines Regulatory Authority
Fixed and variable costs of the devices.
| Costs (US$, 2017) | TruScan RM | Micro PHAZIR RX | 4500a FTIR | Progeny | NIR-S-G1 | PADs |
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| - Cost of devices | 68,750 | 52,250 | 34,724 | 67,449 | 1,539 | 0 |
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| - Replacement cost of the battery | 112 | 506 | N/A | 580 | 30 | N/A |
| - Light bulb | N/A | 300 | N/A | N/A | N/A | N/A |
| - Other material, solvent, and maintenance | N/A | 300 | N/A | N/A | N/A | N/A |
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| 138 | 147 | 358 | 163 | 126 | 126 |
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| 69,000 | 53,503 | 35,082 | 68,192 | 1,695 | 126 |
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| 0.04 | 0.04 | 0.09 | 0.04 | 0.04 | 3.06 |
*Device costs are inclusive of Lao PDR VAT rate of 10%
**Shipment cost was estimated from the average price of DHL Express Worldwide service from Europe (UK) and the USA to Lao PDR based on device weight (June, 2018).
Cost of implementation at country level with two prevalence scenarios.
| Cost US$ (2017) | TruScan RM | Micro PHAZIR RX | 4500a FTIR | Progeny | NIR-S-G1 | PADs |
| Initial Cost | ||||||
| Cost of Devices | 2,887,500 | 2,194,500 | 1,458,414 | 2,832,855 | 64,634 | 0 |
| Shipping Cost | 5,792 | 6,173 | 15,047 | 6,864 | 5,308 | 5,308 |
| Total Initial Cost |
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| Annual Cost | ||||||
| Maintenance cost | 1,176 | 11,613 | - | 6,090 | 315 | - |
| Cost of Inspections | 81,993 | 81,984 | 82,099 | 82,072 | 81,959 | 82,290 |
| Cost of Consumables | 492 | 474 | 1,050 | 648 | 423 | 23,917 |
| Cost of Reference analysis by HPLC | 183,538 | 197,656 | 169,420 | 127,065 | 164,286 | 79,062 |
| Cost of Replacement of suspected SF ACTs | 82,262 | 88,590 | 75,934 | 56,950 | 73,633 | 35,436 |
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| Cost US$ (2017) | TruScan RM | Micro PHAZIR RX | 4500a FTIR | Progeny | NIR-S-G1 | PADs |
| Initial Cost | ||||||
| Cost of Devices | 2,887,500 | 2,194,500 | 1,458,414 | 2,832,855 | 64,634 | 0 |
| Shipping Cost | 5,792 | 6,173 | 15,047 | 6,864 | 5,308 | 5,308 |
| Total Initial Cost |
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| Annual Cost | ||||||
| Maintenance cost | 1,176 | 11,613 | - | 6,090 | 315 | - |
| Cost of Inspections | 81,993 | 81,984 | 82,099 | 82,072 | 81,959 | 82,290 |
| Cost of Consumables | 491 | 474 | 1,050 | 648 | 423 | 23,917 |
| Cost of Reference analysis by HPLC | 63,532 | 70,592 | 56,473 | 35,296 | 55,190 | 28,237 |
| Cost of Replacement of suspected SF ACTs | 28,475 | 31,639 | 25,311 | 15,820 | 24,736 | 12,656 |
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*Device costs are inclusive of Lao PDR VAT rate at 10%.
** Shipping cost was estimated from the average price of DHL Express Worldwide service from Europe (UK) and the USA to Lao PDR based on device weight.
§Cost of inspections was estimated based on the total time spent for overall inspections (visual inspections) and additional time spent for the test by each device.
ßCost of consumables was estimated from additional material used including reagent and cleaning wipes for the test by each device.
†Cost of reference analysis was estimated from the number of samples sent to validate with HPLC from suspected substandard and falsified (SF) samples as suggested by the device screening result.
∑ Cost of replacement was estimated from cost of the whole batch of ACTs that require replacement with genuine ACTs at the pharmacy outlet due to a suspected SF batch as indicated by the device screening results.
Fig 2Cost of introducing post-market surveillance at country level by cost category under (A) Cost of introduction by component under a high prevalence scenario, (B) Cost of introduction by component excluding procurement costs under a high prevalence scenario, (C) Cost of introduction by component under the lower prevalence scenario, (D) Cost of introduction by component excluding procurement costs under the lower prevalence scenario.
Fig 3Incremental costs and effects of inspection with a 1-sample strategy in (A) high prevalence scenario; 20% substandard and 20% falsified and in (B) lower prevalence scenario; substandard 10% and falsified 5%, compared with visual inspection. The diagonal line represents the Willingness to pay threshold at US$ 2,353, Lao PDR GDP per capita).
Country level costs and effects in high and lower prevalence scenario per device with a 1-sample strategy compared with visual inspection ranked by descending net monetary benefit (NMB, US$).
DALYs—disability adjusted life years. ICER—incremental cost-effectiveness ratio.
| Device name | Cost | DALYs | Incremental Cost | DALY averted | ICER | NMB |
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| Baseline | 81,900 | 1,111.7 | ||||
| NIR-S-G1 | 334,541 | 464.9 | 252,641 | 647 | 391 | 1,269,333 |
| MicroPHAZIR RX | 818,129 | 333.5 | 736,229 | 778 | 946 | 1,094,896 |
| 4500a FTIR | 623,195 | 444.7 | 541,295 | 667 | 811 | 1,028,241 |
| PADs | 270,838 | 667.0 | 188,938 | 445 | 425 | 857,419 |
| TruScan RM | 927,883 | 389.1 | 845,983 | 723 | 1,171 | 854,348 |
| Progeny | 839,551 | 611.4 | 757,651 | 500 | 1,514 | 419,501 |
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| Baseline | 81,900 | 444.7 | ||||
| NIR-S-G1 | 176,548 | 227.4 | 94,648 | 217 | 436 | 416,640 |
| PADs | 148,161 | 333.5 | 66,261 | 111 | 596 | 195,328 |
| 4500a FTIR | 459,626 | 222.3 | 377,726 | 222 | 1,699 | 145,452 |
| MicroPHAZIR RX | 634,114 | 166.8 | 552,214 | 278 | 1,987 | 101,759 |
| TruScan RM | 754,091 | 194.6 | 672,191 | 250 | 2,687 | -83,615 |
| Progeny | 706,651 | 305.7 | 624,751 | 139 | 4,496 | -297,765 |
Fig 4Incremental costs and effects of all sampling strategies (1, 2, or 3-samples per drug per inspection) under (A) high prevalence scenario and (B) lower prevalence scenario. The diagonal line represents the Willingness to pay threshold at US$ 2,353, Lao PDR GDP per capita.
Country level costs and effects in high and lower prevalence scenario per device and per different sample strategy compared with visual inspection ranked by descending net monetary benefits (NMB, US$).
DALY—disability adjusted life year. ICER—incremental cost-effectiveness ratio.
| High prevalence scenario | ||||||
| Rank | Device | Strategy | Incremental Cost | DALY averted | ICER | NMB |
| 1 | NIR-S-G1 | 2-sample | 521,578 | 814.4 | 640 | 1,394,582 |
| 2 | NIR-S-G1 | 3-sample | 816,210 | 914 | 893 | 1,334,537 |
| 3 | NIR-S-G1 | 1-sample | 252,641 | 646.8 | 391 | 1,269,333 |
| 4 | MicroPHAZIR RX | 2-sample | 1,038,137 | 945 | 1,099 | 1,185,372 |
| 5 | 4500a FTIR | 2-sample | 804,136 | 815.3 | 986 | 1,114,185 |
| 6 | MicroPHAZIR RX | 1-sample | 736,229 | 778.2 | 946 | 1,094,896 |
| 7 | MicroPHAZIR RX | 3-sample | 1,351,730 | 1,028.40 | 1,314 | 1,067,970 |
| 8 | 4500a FTIR | 3-sample | 1,099,001 | 914.1 | 1,202 | 1,051,844 |
| 9 | 4500a FTIR | 1-sample | 541,295 | 667 | 811 | 1,028,241 |
| 10 | TruScan RM | 2-sample | 1,130,917 | 884.8 | 1,278 | 950,897 |
| 11 | TruScan RM | 3-sample | 1,439,046 | 979.3 | 1,469 | 865,301 |
| 12 | PADs | 1-sample | 188,938 | 444.7 | 425 | 857,419 |
| 13 | TruScan RM | 1-sample | 845,983 | 722.6 | 1,171 | 854,348 |
| 14 | PADs | 2-sample | 326,192 | 444.7 | 734 | 720,166 |
| 15 | PADs | 3-sample | 463,445 | 444.7 | 1,042 | 582,912 |
| 16 | Progeny | 1-sample | 757,651 | 500.3 | 1,514 | 419,501 |
| 17 | Progeny | 2-sample | 917,220 | 551.2 | 1,664 | 379,827 |
| 18 | Progeny | 3-sample | 1,098,954 | 597.9 | 1,838 | 307,997 |
| Low prevalence scenario | ||||||
| Rank | Device | Strategy | Incremental Cost | DALY averted | ICER | NMB |
| 1 | NIR-S-G1 | 2-sample | 199,405 | 296.2 | 673 | 497,626 |
| 2 | NIR-S-G1 | 3-sample | 318,591 | 345.9 | 921 | 495,217 |
| 3 | NIR-S-G1 | 1-sample | 94,648 | 217.3 | 436 | 416,640 |
| 4 | 4500a FTIR | 2-sample | 481,535 | 296.5 | 1,624 | 216,037 |
| 5 | 4500a FTIR | 3-sample | 601,355 | 345.9 | 1,739 | 212,478 |
| 6 | PADs | 1-sample | 66,261 | 111.2 | 596 | 195,328 |
| 7 | MicroPHAZIR RX | 2-sample | 675,210 | 361.3 | 1,869 | 174,955 |
| 8 | 4500a FTIR | 1-sample | 377,726 | 222.3 | 1,699 | 145,452 |
| 9 | MicroPHAZIR RX | 3-sample | 804,050 | 403 | 1,995 | 144,211 |
| 10 | PADs | 2-sample | 118,805 | 111.2 | 1,069 | 142,784 |
| 11 | MicroPHAZIR RX | 1-sample | 552,214 | 277.9 | 1,987 | 101,759 |
| 12 | PADs | 3-sample | 171,349 | 111.2 | 1,541 | 90,240 |
| 13 | TruScan RM | 2-sample | 786,713 | 331.2 | 2,375 | -7,395 |
| 14 | TruScan RM | 3-sample | 912,833 | 378.5 | 2,412 | -22,249 |
| 15 | TruScan RM | 1-sample | 672,191 | 250.1 | 2,687 | -83,615 |
| 16 | Progeny | 2-sample | 676,709 | 164.4 | 4,115 | -289,775 |
| 17 | Progeny | 1-sample | 624,751 | 139 | 4,496 | -297,765 |
| 18 | Progeny | 3-sample | 739,749 | 187.8 | 3,939 | -297,863 |
Fig 5Tornado diagram illustrating one-way sensitivity analyses with a range of plausible parameter values for key model parameters, in a lower prevalence scenario for the NIR-S-G1 device (blue bars represents scenarios with lower parameter estimates, orange bars represent scenarios with the higher parameter estimates, and dotted vertical line represents the cost-effectiveness threshold).
Country level costs and effects in sensitivity analysis when using one device per province instead of one per district per device in lower prevalence scenario with a 1-sample strategy compared with visual inspection in descending order of net monetary benefit (NMB, US$).
DALY—disability adjusted life year. ICER—incremental cost-effectiveness ratio.
| Name | Cost | DALYs | Incremental Cost | DALY averted | ICER | NMB |
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| Baseline | 81,900 | 444.7 | ||||
| MicroPHAZIR RX | 238,192 | 166.8 | 156,292 | 277.9 | 562 | 497,681 |
| NIR-S-G1 | 164,003 | 227.4 | 82,103 | 217.3 | 378 | 429,185 |
| TruScan RM | 243,491 | 194.6 | 161,591 | 250.1 | 646 | 426,985 |
| 4500a FTIR | 200,016 | 222.3 | 118,116 | 222.3 | 531 | 405,062 |
| Progeny | 202,028 | 305.7 | 120,128 | 139.0 | 864 | 206,859 |
| PADs | 147,226 | 333.5 | 65,326 | 111.2 | 588 | 196,263 |
Budget impact analysis under high and low prevalence scenario with a 1-sample strategy across all 42 districts.
| Cost US$ (2017) | TruScan RM | Micro PHAZIR RX | 4500a FTIR | Progeny | NIR-S-G1 | PADs |
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| High prevalence scenario | ||||||
| Cost for the 1st year | 3,242,752 | 2,580,990 | 1,801,964 | 3,112,544 | 390,558 | 226,014 |
| Cost for subsequent years (2nd-5th year) | 349,460 | 380,317 | 328,503 | 272,825 | 320,615 | 220,706 |
| Total cost (five years) |
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| Low prevalence scenario | ||||||
| Cost for the 1st year | 3,068,959 | 2,396,975 | 1,638,395 | 2,979,644 | 232,565 | 152,408 |
| Cost for subsequent years (2nd-5th year) | 175,667 | 196,302 | 164,934 | 139,925 | 162,623 | 147,099 |
| Total cost (five years) |
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