Costing the implementation of public health interventions in resource-limited settings: a conceptual framework

Abstract

Background
Failing to account for the resources required to successfully implement public health interventions can lead to an underestimation of costs and budget impact, optimistic cost-effectiveness estimates, and ultimately a disconnect between published evidence and public health decision-making.

Methods
We developed a conceptual framework for assessing implementation costs. We illustrate the use of this framework with case studies involving interventions for tuberculosis and HIV/AIDS in resource-limited settings.

Results
Costs of implementing public health interventions may be conceptualized as occurring across three phases: design, initiation, and maintenance. In the design phase, activities include developing intervention components and establishing necessary infrastructure (e.g., technology, standard operating procedures). Initiation phase activities include training, initiation of supply chains and quality assurance procedures, and installation of equipment. Implementation costs in the maintenance phase include ongoing technical support, monitoring and evaluation, and troubleshooting unexpected obstacles. Within each phase, implementation costs can be incurred at the site of delivery (“site-specific” costs) or more centrally (“above-service” or “central” costs). For interventions evaluated in the context of research studies, implementation costs should be classified as programmatic, research-related, or shared research/program costs. Purely research-related costs are often excluded from analysis of programmatic implementation.

Conclusions
In evaluating public health interventions in resource-limited settings, accounting for implementation costs enables more realistic estimates of budget impact and cost-effectiveness and provides important insights into program feasibility, scale-up, and sustainability. Assessment of implementation costs should be planned prospectively and performed in a standardized manner to ensure generalizability.

Full text

C O M M E N T A R Y Open Access
Costing the implementation of public
health interventions in resource-limited
settings: a conceptual framework
Hojoon Sohn
*†
, Austin Tucker
†
, Olivia Ferguson
†
, Isabella Gomes
†
and David Dowdy
†
Abstract
Background: Failing to account for the resources required to successfully implement public health interventions
can lead to an underestimation of costs and budget impact, optimistic cost-effectiveness estimates, and ultimately
a disconnect between published evidence and public health decision-making.
Methods: We developed a conceptual framework for assessing implementation costs. We illustrate the use of this
framework with case studies involving interventions for tuberculosis and HIV/AIDS in resource-limited settings.
Results: Costs of implementing public health interventions may be conceptualized as occurring across three
phases: design, initiation, and maintenance. In the design phase, activities include developing intervention
components and establishing necessary infrastructure (e.g., technology, standard operating procedures). Initiation
phase activities include training, initiation of supply chains and quality assurance procedures, and installation of
equipment. Implementation costs in the maintenance phase include ongoing technical support, monitoring and
evaluation, and troubleshooting unexpected obstacles. Within each phase, implementation costs can be incurred at
the site of delivery (“site-specific”costs) or more centrally (“above-service”or “central”costs). For interventions
evaluated in the context of research studies, implementation costs should be classified as programmatic, research-
related, or shared research/program costs. Purely research-related costs are often excluded from analysis of
programmatic implementation.
Conclusions: In evaluating public health interventions in resource-limited settings, accounting for implementation
costs enables more realistic estimates of budget impact and cost-effectiveness and provides important insights into
program feasibility, scale-up, and sustainability. Assessment of implementation costs should be planned
prospectively and performed in a standardized manner to ensure generalizability.
Keywords: Implementation strategies, Costs of implementation, Economic evaluation, Decision-making, Tuberculosis
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* Correspondence: hsohn6@jhu.edu
†
Hojoon Sohn, Austin Tucker, Olivia Ferguson, Isabella Gomes and David
Dowdy contributed equally to this work.
Department of Epidemiology, Johns Hopkins Bloomberg School of Public
Health, 615 N. Wolfe Street E6531, Baltimore, MD 21205, USA
Sohn et al. Implementation Science (2020) 15:86
https://doi.org/10.1186/s13012-020-01047-2

Introduction
Economic evaluations are frequently used to inform
prioritization of health interventions and resource alloca-
tion for public health [1]. Unfortunately, most existing
economic evaluations of public health interventions have
done so retrospectively [2], thereby limiting their ability to
fully assess the costs of implementation, especially during
the early stages of design and initiation. A growing num-
ber of studies are exploring these implementation costs,
but many continue to do so in retrospective fashion, and
interventions in resource-limited settings—where imple-
mentation costs may represent a disproportionate fraction
of total intervention costs—aresorelyunder-represented
[2]. As such, most published economic evaluations may
have greatly underestimated the costs of public health in-
terventions, particularly those studied in resource-limited
settings. A framework for considering and prospectively
collecting implementation costs could therefore greatly
improve economic evaluations of public health interven-
tions in the coming years.
To illustrate, the Avahan initiative was a complex inter-
vention to prevent HIV transmission across six Indian
states that included peer outreach, clinical services, condom
distribution, safe needle exchange, and community
mobilization [3]. A cost-effectiveness analysis estimated that
Avahan cost $46 per disability-adjusted life year (DALY)
averted [4]. However, approximately two thirds of overall
costs were incurred at the “above-service”level—involving
institutions above or ancillary to the provision of care (e.g.,
government, non-governmental organization (NGO), or
multilateral institution support or infrastructure for facili-
tating provision of care). Had these costs of implementation
not been counterbalanced by four years of service delivery,
the cost per person reached could have been four times
higher—with qualitatively important cost-effectiveness im-
plications [5]. Such implementation costs are frequently
neglected in economic evaluations, leading to underesti-
mated costs, optimistic cost-effectiveness estimates, and a
disconnect between published evidence and public health
decision-making. This disconnect is particularly stark in
settings where resources are most constrained.
Another illustration of the importance of implementation
costing is the recently published PopART (HPTN 071) trial
of universal testing and treatment for HIV in South Africa
and Zambia [6]. This trial, conducted over 5 years, mobi-
lized 740 community HIV care providers working in pairs
(each pair covering approximately 500 households) to
provide comprehensive health services—from HIV
counseling and rapid testing to screening for tuberculosis
(TB) and sexually transmitted infections—during annual
household visits. This multifaceted intervention reduced
HIV infection by 30% but required extensive programmatic
coordination and administrative management, including
rigorous re-training and human resource management,
planning of daily household visits and periodic community
engagement campaigns, HIV testing drives, and centralized
coordination of study activities (e.g., obtaining regulatory
approvals, provision of security, and maintenance of a
stable procurement and supply chain) [7]. Costs associated
with the implementation of these complex and compre-
hensive activities—often neglected in cost-effectiveness
analyses—may make the start-up of health interventions
unaffordable or infeasible. This, in turn, would result in
substantial waste of resources if interventions are poorly
maintained or not sustained.
To provide decision-makers with an honest appraisal
of the potential costs and benefits of any health inter-
vention, it is critical to document the full range of costs
required for programmatic implementation, including
the costs of intervention design and local adaptation,
initiation and scale-up, and maintenance/sustainability.
While consideration of implementation costs is universally
relevant, these costs may be proportionally more import-
ant in settings where resources are highly constrained.
Here, we use the example of peripheral diagnostic testing
for TB as a case study to illustrate the importance of
evaluating costs throughout the implementation process
Contributions to the literature
Economic evaluations have long been used to prioritize
health interventions in resource-limited settings. However,
these analyses often fail to capture the resources required to
successfully implement interventions and thus may greatly
underestimate the actual economic costs of the intervention.
Most existing studies in the health economics literature in
the context of implementation science are retrospective or
‘ex-post’in nature; methods and examples of evaluating
these costs prospectively are limited, particularly in resource
limited settings.
Using recent examples from the literature, we highlight the
importance and potential magnitude of costs associated
with implementation of public health interventions in
resource constrained settings.
We also provide a conceptual framework that details the
types of economic resources utilized during the design,
initiation, and maintenance phases of implementation and
the implications of neglecting implementation costs in
evaluating the cost-effectiveness of interventions in resource-
limited settings.
Such a framework provides greater insight into the need for
implementation costing practices for more accurate
economic evaluation and budget impact analysis as well as
insights into program feasibility, scale up and sustainability.
Sohn et al. Implementation Science (2020) 15:86 Page 2 of 8

and to propose a structured method for investigating these
costs.
Peripheral diagnostic testing for TB: a case study of
implementing a novel health intervention in settings of
severe resource constraints
An estimated 13–18% of patients diagnosed with TB in
Africa and Asia are lost to follow-up before starting
treatment [8]. The current standard of care for TB diag-
nosis involves molecular testing requiring equipment
(e.g., four-module GeneXpert® instruments) that often
cannot be maintained at the point of care [9]. Novel
tests—including more portable devices (e.g., GeneXpert®
Edge) and simpler assays (e.g., lateral-flow detection of
urine lipoarabinomannan [LF-LAM])—that can diagnose
TB at the point of treatment have been prioritized as a
means of reducing diagnostic delays and losses to fol-
low-up [10]. Cost-effectiveness analyses of peripherally
implemented TB diagnostic tests are emerging [11]; how-
ever, existing analyses may not fully account for the costs
required to implement these novel assays in practice.
Costing the implementation process: a framework
Similar to many consumer products, public health inter-
ventions can be conceptualized as having a “product life
cycle,”with well-defined stages—design, launch, growth,
maturity, and decline—from introduction to removal
from the “market”[12]. Considering each of these stages
is critical to the financial success of consumer prod-
ucts—and this is equally true for public health interven-
tions. Although the systems required for each product
life cycle phase differ, the costing of systems for launch
often overlaps with those for design (preparation for
launch) or growth (which starts immediately after
launch)—and the decline phase acknowledges that every
product (or intervention) has a finite time horizon. Thus,
in mapping the structure of the product life cycle to the
costing of public health interventions, one can delineate
three stages: design and adaptation to the local context
(“design phase”including preparation for launch), initial
implementation and scale-up (“initiation phase”corre-
sponding to launch and growth), and ongoing activities
to ensure intervention sustainability (“maintenance
phase”corresponding to maturity and forestalling of
decline) [13].
As illustrated in Fig. 1a, the implementation process is
not necessarily unidirectional. Rather, the various phases
of implementation inform one another, especially as
interventions are adapted from one context to another
or expanded in size or scope. For example, experiential
knowledge attained during the initiation phase in one
setting may inform the re-design of protocols for the
design phase in a different cultural context. Similarly,
the maintenance phase of an intervention in an “early
adopter”country may inform policymakers and re-
searchers about the potential sustainability of the inter-
vention and influence considerations about design and
initiation in other regions or countries. As such, it is
important to individually estimate the cost of each stage
of the implementation process—and to illustrate how
those estimates depend on key assumptions (e.g., scale
of implementation, local market rates for human re-
sources and other costs)—so that those estimates can be
generalized to other contexts where existing knowledge
and infrastructure may be more or less complete.
In addition to the costs incurred at different phases of
implementation, costs can be incurred at the site of
delivery (“site-specific”costs; containing administrative
efforts from the service delivery facility—e.g., clinic or
hospital administration) or more centrally (“above-ser-
vice”or “central”costs; services such as support from a
district health office [DHO], NGO, or Ministry of Health
[MOH]). Furthermore, health interventions are often
evaluated in the context of research studies or evaluation
programs, necessitating a differentiation between costs
required for programmatic implementation and those
incurred purely for the purposes of research or evaluation
(the latter being less relevant to the cost-effectiveness of the
intervention itself). Importantly, some degree of monitoring
and evaluation is necessary for effective implementation
and should therefore be included as a programmatic cost;
however, the costs incurred by research studies and other
knowledge generation activities often exceed this baseline
requirement and may vary depending on the type of
intervention being considered. As such, it is important to
prospectively monitor and categorize costs as purely
research-related (i.e., likely not to be incurred during subse-
quent implementation in other settings) versus necessary
for programmatic implementation (even if those costs rep-
resent “research”activities) to facilitate subsequent analyses.
Table 1provides examples of costs that may be incurred
acrossthethreephasesofimplementation, site-specific ver-
sus central locations, and programmatic versus research
purposes—using the example of an ongoing cluster
randomized trial of peripheral versus central molecular TB
testing(theXpertPerformanceEvaluationforLinkageto
Tuberculosis Care [XPEL TB] trial) [14]. As illustrated in
panel b of Fig. 1,“above-service”costs in the design and
initiation phases tend to represent a greater proportion of
total costs. Thus, consideration of these costs—while always
important—is most critical when the costs of design and
initiation are greater relative to the costs of delivery (e.g., in-
terventions that are scaled-up to a smaller population),
when interventions are being considered by decision-
makers (e.g., politicians) with shorter time horizons, when
interventions are expected to change in scope or cost with
time (e.g., through price reductions or release of new
competing interventions), or when interventions are not
Sohn et al. Implementation Science (2020) 15:86 Page 3 of 8

immediately affordable. These situations account for a large
fraction of health interventions being considered for imple-
mentation in resource-limited settings. Furthermore, most
public health interventions in resource-limited settings are
not sustained indefinitely. Thus, rigorously measuring the
costs of design and implementation and weighing those
against the expected duration of the maintenance phase
can improve our understanding of the costs and sustain-
ability of public health interventions in terms of their life
cycles. We now provide examples of costs that might be
incurred at each phase of the implementation process
(summarized in Table 2).
Design phase
Implementation costs incurred during the design and
adaptation of health interventions may include crafting
of appropriate policies and algorithms, obtaining polit-
ical and administrative approvals, developing necessary
infrastructure, engagement of relevant stakeholders, and
pilot testing in the local context. Where these costs are
large and must be incurred before scale-up is certain,
they may represent a majority of the total cost of the
intervention. For example, in a trial of mobile Health-
facilitated home-based contact investigation for TB in
Uganda, a software package was required to generate
short messaging service (SMS) reminders to facilitate
home-based screening, incurring large up-front costs for
an initial service contract and adaptation to the Ugandan
telecommunications infrastructure [15]. While this inter-
vention was only delivered to 372 households (919 con-
tacts screened), the cost of designing and developing the
intervention ($137 per contact screened, of which $90
Fig. 1 Simplified illustration of stages, activities, resource classification, and assessment of costs of public health intervention implementation
process. aA description of the implementation process listing key components of each phase that may carry additional resource requirements is
provided. Light blue arrows represent potential feedback loops between phases. bAn illustration of resource and cost classification of the public
health intervention implementation process. At each phase, resource-use for relevant activities is classified based on the location (above site vs.
site-specific) of activity and degree to which activities are programmatic versus research specific. Sizes of each square (different shades of
blue)—arbitrarily assigned for the purposes of demonstration—represent the corresponding size of each activity category. The increasing size of
light-shaded boxes to the right indicate an increasing programmatic component as the study progresses into the maintenance phase
Sohn et al. Implementation Science (2020) 15:86 Page 4 of 8

Table 1 Descriptions of key activities by study phases (XPEL study example)
Classification of activities Research or knowledge generation costs
a
Programmatic costs Shared research/program costs
Design phase
Central •Ministry of Health (MoH), provincial,
and district level approvals for the
research study
•Institutional Review Board approvals
•Development of study CRFs (clinical
outcomes)
•Development of research database
(RedCap* program)
•Development of study protocols
•International collaborator site visits
and periodic study calls
•Central procurement of GeneXpert
machines, related equipment (e.g.,
solar panels and external batteries),
Xpert Ultra cartridges, and
associated supplies
•Development of SOPs* for Xpert
testing, troubleshooting and QA/
QC manuals, and management of
testing equipment
•Recruitment of study staff
•Focus group discussions
Site-specific •Site visits for site selection
•Review of clinical and laboratory
data
•N/A •Sensitization meetings at district
health office and potential study
sites
•Pilot studies conducted at select
potential study sites
Initiation phase
Central •Establish clinical and laboratory data
monitoring (including National TB
Reference Laboratory)
•Management of regulatory
processes with MoH
•Development of data collection
plans for health economics study
•International collaborator site visits
and periodic study calls
•Development of plans and
organization of site visit and
training
•Stock management (medical and
laboratory consumables and Xpert
cartridges)
•Study database management
(clinical and programmatic)
•Data quality checks
•Weekly study call
(implementation issues, study
data checks, etc.)
Site-specific •Management of provincial, district
level regulatory processes
•Installation of solar panel and
GeneXpert equipment (including
GX Alert system)
•Distribution of Xpert cartridges and
laboratory consumables
•Training of laboratory personnel
and technical support for Xpert
testing
•Site sensitization meetings (w/
routine clinic staff) at both
intervention and control sites
•Initial participant enrolment
•Establishment of data collection
and follow-up plans
•Interim adjustments in
implementation plans (including
addition or exclusion of sites)
•Recruitment of study contact
persons at each site (for data
monitoring and study logistics
purposes)
Maintenance phase
Central •Management and monitoring of
study data
•International collaborator site
visits and periodic study calls
•Data analyses and reporting
•Stock management (medical and
laboratory consumables and Xpert
cartridges)
•Site visit organizations and
communications
•Study database management
(clinical and programmatic)
•Central database data review
and quality checks
•Weekly study call
(implementation issues, study
data checks, etc.)
•Central study team human
resource management
Site-specific •Site-specific data issue
troubleshooting
•Ongoing technical support and
troubleshooting (for GeneXpert and
Solar panel equipment)
•Distribution of Xpert cartridges and
laboratory consumables
•Procurement and replacement of
key equipment (if broken)
•QA/QC of Xpert testing
•Review of GX Alert data
•Periodic EQA and re-training for
Xpert testing
•Quarterly site visit
•Participant enrolment
•Adjustments in site-specific
operations
•Ongoing human resource
management at study sites
•Data monitoring and quality
checks
a
Research or knowledge generation costs that would be required for programmatic implementation in other settings (for example, ongoing monitoring
and evaluation) should be clearly delineated and considered as programmatic costs in most analyses
SOP Standard operation procedure, QA Quality assurance, QC Quality control, EQA External quality control, GX Alert System software system to centrally
report site-specific Xpert testing statistics, equipment and testing troubleshooting, and testing operations
Sohn et al. Implementation Science (2020) 15:86 Page 5 of 8

was for software development) overshadowed the cost of
intervention delivery ($54 per contact screened) [16].
This initial outlay for intervention design could be
partially counterbalanced by scale-up to a broader popu-
lation but would probably be incurred again if the inter-
vention were implemented in a different country with a
different telecommunications system. Importantly, these
costs might vary considerably across countries, regions,
and facilities with different levels of underlying infrastruc-
ture—and these differences would need to be considered by
both researchers (aiming to produce generalizable know-
ledge) and implementers (aiming to accurately estimate
design costs in their unique contexts). Failure to consider
the cost of designing the intervention and adapting it to the
local context would have resulted in both a dramatic
overestimation of cost-effectiveness and an incomplete
understanding of the generalizability of cost and cost-
effectiveness estimates for implementation of the interven-
tion in other settings.
Initiation phase
As interventions are initially rolled out and scaled-up,
many types of implementation costs (e.g., training mate-
rials and personnel, infrastructure necessary to launch
implementing teams) are incurred up-front. These fixed
costs often do not vary with the level of service output.
The contribution of up-front costs to the overall cost
and cost-effectiveness of a program may vary consider-
ably across implementation sites depending on each
site’s operational and infrastructural capacity and imple-
mentation outcomes such as program reach (i.e., the
number and representativeness of people engaged by the
program) [17]. These costs are often not adequately con-
sidered in traditional cost-effectiveness estimates. This is
particularly problematic when variable costs (e.g., med-
ical consumables, test kits, and unit staffing costs) to
deliver the intervention are low, but the intervention has
high implementation and operating costs. For example,
the Alere Determine
TM
TB LAM Ag assay (LF-LAM) is
a simple dipstick-based diagnostic test for TB that costs
less than $2 per test kit and requires minimal operator
time [18]. Cost-effectiveness analyses have therefore
considered the unit cost of LF-LAM to be between $3
and $4 per test [11]. However, this estimate fails to
account for the “above-service”(and service-level) costs
required to implement LAM—including building costs,
staff salaries, utilities, and supplies necessary for such
activities as preparing clinics and training clinical staff,
coordinating logistics during implementation, assuring
fidelity to (often complex) policy guidance, and estab-
lishing a reliable supply chain [10]. After incorporating
these costs, the unit cost of LF-LAM in South Africa
was estimated at over $23 per patient tested—approxi-
mately seven-fold higher than the simple estimate based
primarily on consumable costs alone [19]. Such underesti-
mates of intervention costs (when costs of implementation
and scale-up are not incorporated) are unfortunately very
common in the scientific literature and lead to reported
cost estimates that do not reflect programmatic realities
on the ground.
Maintenance phase
Although implementation costs are often proportionally
lower during the maintenance phase (Fig. 1b), they
should not be ignored entirely—particularly for interven-
tions that require infrastructure and/or procedures that
require ongoing upkeep or quality assurance. For
example, in the XPEL trial, single-module GeneXpert
devices were installed to enable point-of-treatment
diagnosis at 10 peripheral health centers in Uganda.
Maintaining these devices requires assurance of a stable
electrical supply (e.g., installation and maintenance of
solar panels), backup testing systems for when devices
temporarily fail (which occurred at 6 sites over a 14-
month period), security to prevent theft of computers
and other electronics, service contracts to perform
repairs, routine monitoring and evaluation, maintenance
of a reliable supply chain of diagnostic cartridges, and
external quality assurance to ensure ongoing high-
quality testing by mid-level staff. Corresponding costs
varied from one site to another and when considered in
full, costs associated with the maintenance operations
accounted for > 12% of the total unit cost of peripheral
Xpert testing, even when only considering costs beyond
the initiation phase (unpublished data). As the level of
technology incorporated in new health interventions often
Table 2 Interventions for peripheral diagnosis of tuberculosis (TB) likely to incur large costs in each phase of implementation
Implementation
phase
Application Example
Design phase Interventions needing large capital outlay for
design and adaptation with uncertain scale-up
Implementation of mHealth-facilitated contact investigation for TB requiring
procurement and tailoring of software packages
Initiation phase Simple interventions with low consumable costs
that require changes in policy and workflow
Low-cost lateral-flow LAM assay for TB that necessitates a new supply chain,
clinical algorithms, and training of personnel
Maintenance
phase
Interventions that require continued infrastructure
support and quality control
Molecular diagnosis of TB with equipment (e.g., Xpert MTB/RIF®) that
necessitates service contracts for equipment failure and external quality
assurance of test results
Sohn et al. Implementation Science (2020) 15:86 Page 6 of 8

outpaces the establishment of corresponding infrastruc-
ture in many global settings, explicitly estimating the costs
of maintaining those interventions and ensuring their
sustainability will become increasingly important [20].
A way forward
The examples above help illustrate the importance of
considering costs at each stage of the implementation
process. This structured approach to costing of the imple-
mentation process suggests three priorities for improving
cost-effectiveness analyses of health interventions in
resource-limited settings.
First, cost-effectiveness analyses should not rely entirely
on budgetary information but should explicitly consider
activities and resources required for successful implemen-
tation. Examples of approaches for such implementation
costing include collection of routine activity logs of imple-
menting staff, structured discussions with field personnel
to enable health economists to understand the extent of
resources required for major implementation activities
(e.g., trainings, site initiation), and ongoing documentation
of specific challenges in implementation (e.g., sites in
which implementation failed, staff leaving).
Second, implementation cost data should be classified
by resource type, key activities, phase of implementation
(e.g., as described in Fig. 1), site level (site-specific vs
“above-service”), and as programmatic versus non-
programmatic (research) so that implementation costs
can be generalized to other settings and key drivers of
implementation costs can be identified. In costing the
implementation process, assumptions can often be made
when empiric data are not immediately available—but
appropriate documentation and categorization of data
and assumptions are critical if generalizable knowledge
is to be generated.
Third, costing activities should generally be planned
prospectively before implementation begins (so the process
of implementation can be costed). While retrospective
estimation of implementation costs is often feasible, such
estimates are often subject to recall bias and difficult to
appropriately classify retroactively. Early involvement of
health economists (with experience in empiric costing ac-
tivities) can therefore be very useful in evaluating the costs
of implementation.
One final consideration is whether detailed measure-
ment of implementation costs is justified for a particu-
lar implementation research study. In making this
assessment, investigators should consider two ques-
tions. First, if the intervention is found to be effective,
is implementation likely to be influenced by consider-
ations of cost-effectiveness and/or budget impact?
Second, are there sufficient uncertainties in the costs of
implementing the intervention that an empiric estima-
tionofcostsiswarranted(asopposedtosimplyusing
pre-existing cost estimates from the literature)? In most
cases, the answer to the first question will be yes, and
the answer to the second question will be no, meaning
that an empiric estimation of costs is scientifically justi-
fied. When this is the case, investigators must then
evaluate whether the budget exists to measure these
costs and (given limited financial resources) whether
otherscientificquestionsaremorepressing.
Conclusions
In summary, we argue that the costs of implementing
health interventions in resource-limited settings are often
very substantial, but generally neglected in economic
evaluation. We provide a framework for effectively
conceptualizing and prospectively measuring these costs,
which—if incorporated appropriately—can improve the
linkage between published results of cost-effectiveness
analyses and the realities of implementation in the field.
Acknowledgements
We gratefully acknowledge the teams of the XPEL trial and mHealth TB
contact investigation trial of TB diagnosis in Uganda, as well as the REDART
trial and SNaP trial of interventions to improve delivery of antiretroviral
therapy in Vietnam, from which many of these lessons were distilled.
Authors’contributions
HS and DD conceived the idea of the topic of this manuscript. All authors
contributed equally in writing the initial draft and revising this manuscript.
The author(s) read and approved the final manuscript.
Funding
This work was supported in part by the National Heart, Lung, and Blood
Institute (NHLBI), grant number R01HL138728, to Dr. Dowdy.
Availability of data and materials
Not applicable
Ethics approval and consent to participate
Not applicable
Consent for publication
Not applicable
Competing interests
All authors do not have any interests to declare.
Received: 6 April 2020 Accepted: 16 September 2020
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