Components of Existing National Surgical Site Infection Surveillance Programs Based on a Case Series of Low- and Middle-Income Countries: Building Blocks for Success and Opportunities for Improvement

Abstract

Background:

Surgical site infection (SSI) surveillance programs are recommended to be included in national infection prevention and control (IPC) programs, yet few exist in low- or middle-income countries (LMICs). Our goal was to identify components of surveillance in existing programs that could be replicated elsewhere and note opportunities for improvement to build awareness for other countries in the process of developing their own national surgical site infection surveillance (nSSIS) programs.

Methods:

We administered a survey built upon the U.S. Centers for Disease Control and Prevention's framework for surveillance system evaluation to systematically deconstruct logistical infrastructure of existing nSSIS programs in LMICs. Qualitative analyses of survey responses by thematic elements were used to identify successful surveillance system components and recognize opportunities for improvement.

Results:

Three respondents representing countries in Europe and Central Asia, sub-Saharan Africa, and South Asia designated as upper middle-income, lower middle-income, and low-income responded. Notable strengths described by respondents included use of local paper documentation, staggered data entry, and limited data entry fields. Opportunities for improvement included outpatient data capture, broader coverage of healthcare centers within a nation, improved audit processes, defining the denominator of number of surgical procedures, and presence of an easily accessible, free SSI surveillance training program for healthcare workers.

Conclusions:

Outpatient post-surgery surveillance, national coverage of healthcare facilities, and training on how to take local SSI surveillance data and integrate it within a broader nSSIS program at the national level remain areas of opportunities for countries looking to implement a nSSIS program.

Surgical site infection (SSI) surveillance programs are strongly recommended as a core component of effective national infection prevention and control (IPC) programs, yet few exist in low- or middle-income countries (LMICs).^1,2 Potential benefits of such programs are many and include: data obtained from these programs can be used to quantify burden of SSIs nationally and locally; encourage responsible antibiotic stewardship; establish national quality metrics; identify outbreaks of existing, emerging, re-emerging, or anti-microbial-resistant SSI pathogens; and advocate for additional IPC resources among others.^3,4 In early 2019, the Surgical Infection Society's Global Health Committee performed a cross-sectional survey of LMICs to determine, what if any, national surgical site infection surveillance (nSSIS) programs exist in LMICs.¹ As a corollary to this prior study, we performed a survey to systematically deconstruct the logistical infrastructure of existing nSSIS programs in LMICs. Our goal was twofold: to identify components of surveillance in these existing programs that are successful that could be replicated elsewhere and note opportunities for improvement to build awareness for other countries in the process of developing their own nSSIS programs.

Methods

A cross-sectional survey had previously been performed to evaluate existence of nSSIS in World Bank-defined LMICs.¹ For the five respondents representing countries endorsing presence of a nSSIS program, a long-form follow-up survey was administered (Supplementary Data) between November 2019 and June 2022. This follow-up survey, comprising 10 thematic elements with a total of 58 items, was built upon existing framework for surveillance system evaluation used by the U.S. Centers for Disease Control and Prevention (CDC).^5,6 Thematic elements assessed included: structure, simplicity/flexibility, data quality, acceptability, sensitivity, predictive value, representativeness, timeliness, stability, and the impact of the coronavirus disease 2019 (COVID-19) pandemic on surveillance system function. A suitable respondent was defined as previously described; only respondents participating in the initial survey were included.¹ Respondents were approached at least three times by two authors until a response was achieved. Clarification of survey responses was performed by five authors (J.D.F., A.B., A.S., T.T., and J.C.). Respondent countries were de-identified to ensure respondent anonymity. Summative description of existing nSSIS programs was performed. Qualitative analyses of survey responses by thematic elements were used to identify successful surveillance system components and recognize opportunities for improvement. Our survey was provided in both English and Spanish editions as needed. Stanford Institutional Review Board approval was sought, and this study and considered exempt.

Results

Of the five respondents from countries with nSSIS identified in our initial survey, three respondents were willing and able to fill out the long-form survey. The respondents from the two countries that did not provide additional data were contacted by two authors on three separate occasions; receipt was acknowledged but the respondents reported insufficient bandwidth or time to complete the long-form survey. Of the countries that completed the long-form survey, one country was upper middle-income, one was lower middle-income, and one was low-income, and countries in Europe and Central Asia, sub-Saharan Africa, and South Asia were represented. The combined population of respondent countries was 32.8 million persons (0.5% of total LMICs population for 2019). All nSSIS programs were reported as being a part of the countries' IPC program. Inception years for nSSIS programs ranged from 2014 to 2017. Qualitative synthesis of survey responses by thematic element are reported (Table 1).

Table 1.

Summary of Thematic Elements of Existing nSSIS Programs in LMICs

Thematic element of a surveillance program	Summary
Structure	Strengths Data collected at local level on paper decreasing reliance on continual access to electricity National laboratory present
Structure	Opportunities No independent budget for nSSIS program National laboratory not linked to reporting system
Simplicity/Flexibility	Strengths Data collection limited to patient demographics, type of surgery, hospital identifying information, and basic outcome measures Use of common and straightforward analytic software
Simplicity/Flexibility	Opportunities No standardized minimum basic outcome measures per case
Data Quality	Strengths Standardized definition for SSI used Clear and consistent expectation establishing the individual or group collecting local data and transmitting it centrally
Data Quality	Opportunities Need to provide definition of SSI in visible, central site such as MoH website Improve outpatient data capture Implement rigorous data audit process for local and national data
Acceptability	Strengths nSSIS surveillance protocol is publicly visible and available
Acceptability	Opportunities Publicly acknowledge nSSIS program and provide benchmarks nationally to healthcare workforce and public Establish online access to surveillance system results Standardize data reporting format of local data reported nationally Identify system to improve participation from both private and public healthcare facilities
Sensitivity	Strengths Post-discharge surveillance is present
Sensitivity	Opportunities Low capture rate for post-discharge surveillance Create mechanism for linking patients across healthcare entities and systems Identify priority threats that mandate national reporting
Predictive Value	Strengths Exposed population defined
Predictive Value	Opportunities Determine and benchmark post-discharge follow-up percentages Develop reproducible process for risk stratification
Representativeness	Strengths Technical IPC team present to help support nSSIS program
Representativeness	Opportunities Develop standardized nSSIS IPC training for LMIC context
Timeliness	Strengths Annual or more frequent reporting Reports provided to general public
Timeliness	Opportunities Ensure governing body is capable responding to threats or induce change rapidly when needed
Stability and impact of COVID-19	Strengths nSSIS programs survived COVID-19 pandemic despite being profoundly impacted
Stability and impact of COVID-19	Opportunities Establish plan for surveillance system re-evaluation

nSSIS = national surgical site infection surveillance programs; SSI = surgical site infection; LMICs = low- or middle-income countries; MoH = Ministry of Health; IPC = infection prevention and control; COVID-19 = coronavirus disease 2019.

Structure

Two respondents described nSSIS program objectives as defined and incorporated within the national healthcare strategy. All three respondents explained that data were stored and transmitted at the local level using paper methods. One respondent related that data transmission from the local level to the national level used only paper methods whereas two respondents reported that data were transmitted using electronic methods to the nSSIS. Two respondents reported data are transmitted from the local level in aggregate to the nSSIS, whereas one respondent reported that individual patient data are transmitted nationally after being de-identified. For all three countries, electricity or Internet was described as being required. However, all three respondents noted that one of the benefits of batch submission by e-mail was that “if the electricity is lost, you do it (data transmission) when it is back….easy!!!” and that availability of electricity is “usually not an issue because data are transmitted locally by e-mail annually.”

All three respondents stated there was no independent budget for the nSSIS program: either the nSSIS program must compete with other IPC priorities for funding or hospitals “pay out of pocket” to support data acquisition and transmission to the national level. Two respondents reported a national reference laboratory is available, with one respondent reporting that “the national reference laboratory staff form a key component of the surveillance team” whereas the other respondent noted that the national reference laboratory only reports laboratory data back on “a case-by-case basis.”

Simplicity/flexibility

Two respondents provided line lists of collected data that included: patient demographics, hospital location, type of surgery, and presence and characterization (superficial/deep/organ space⁷) of SSI. One respondent reported hospital length-of-stay was recorded, and one respondent reported patient comorbidities were collected in addition to the previously listed items. For the two countries that use electronic data transmission systems, aggregate data was sent using e-mail and a Microsoft Excel file (Microsoft, Redmond, WA). Two countries used Microsoft Excel for all data analysis, and in all cases the Ministry of Health was responsible for data aggregation and analysis.

Data Quality

Two respondents reported that a separate and published definition for an SSI existed, and was “based upon the CDC/NHSN [National Healthcare Safety Network] definition.” One country reported using a separate SSI definition, which was bundled into the definition of a healthcare-associated infection. Two respondents reported the SSI definition was published, although one respondent noted that this published definition existed only within a specific surveillance protocol and was not widely available. The other respondent reported the SSI definition was publicly available on the Ministry of Health (MoH) website. All three respondents reported that both inpatient and outpatient SSI data are collected although all three respondents expressed concern about outpatient data capture and confirmed most reported data are obtained from inpatients.

The individual(s) responsible for data collection varied between countries. One respondent reported each hospital had a team comprised of the hospital microbiologist, a nurse, and a designated infection control individual who collected and reported local data. Another respondent noted the hospital epidemiologist was responsible for data acquisition and reporting nationally. The third respondent reported that each hospital is required to have an IPC committee that is responsible for local data acquisition and national reporting.

Local data validation techniques varied, from an annual audit performed by the national IPC program to local team members performing “validation by cross-checking each other and a post-survey discussion.” Once the data have been received nationally, national data quality confirmation existed along a spectrum from an annual audit performed in person by national authorities to a bi-annual “check of the soft copy entry with the paper form, and a call to respective hospitals for conformation of data if required.” One respondent reported local data are not validated by the national surveillance team. All three respondents reported they were unaware of any internal data validation process performed by the nSSIS program to ensure data integrity after collation at the national level.

Acceptability

Two respondents reported the nSSIS protocol is publicly available, and the respondent reporting that the surveillance protocol was not publicly available did comment that copies of the protocol are provided to each health center and can be publicly displayed at the discretion of local health centers. All three respondents stated there was no availability to the surveillance system online, other than through transmission of data by email. All three respondents described the actual reporting format was left to the discretion of the reporting facilities. Two respondents reported only public hospitals are required to participate in surveillance; the other respondent noted that although public and private hospitals are required to participate, only public hospitals submit data. Respondents reported only 4%–14% of healthcare facilities reported data, despite mandatory data reporting requirements. No respondents reported national incentives for data reporting, nor were penalties for not reporting enforced. All three respondents reported that consent from individual patients for surveillance was not obtained.

Sensitivity

One respondent reported that no post-discharge surveillance is performed. The other two respondents commented that although post-discharge surveillance is performed, it is “reported only for those coming back to the health center (i.e., where the procedure was performed)” or “only if a patient reports back to the hospital or the provider (i.e., performing the procedure).” Both respondents who reported the presence of post-discharge surveillance noted that no national standardization exists for performing post-discharge surveillance. All three respondents reported that if a patient reports to a different facility with an SSI, there is not an automated way to link that infection to their original surgery. All three respondents reported that there were no organisms or resistance patterns that mandated national reporting.

Predictive value

Two respondents reported the exposed population was defined by the nSSIS program as every patient who underwent surgery at a given hospital, while one respondent reported the denominator (total number of patients who underwent surgery at a given hospital or health facility) is not reported. One respondent reported that SSI reporting only occurs for cesarean deliveries and general surgical procedures. All three respondents reported that post-discharge follow-up percentages are not reported. Two respondents reported no performance of patient risk stratification, whereas one respondent reported risk stratification exists within a national protocol “but has been difficult to implement.”

Representativeness

All three respondents stated that no consistent programs are in place to support health care worker education on SSIs, and healthcare workers rely on “a small budget from the MoH and occasional funding from the World Health Organization (WHO) country office” to perform SSI education at the national or local level. No national curricula were reported to be in place for SSI education by any respondent. One respondent reported that “at the local level, visiting institutions” supply the majority of healthcare worker SSI education. All three respondents reported that a technical national IPC team was present, but that these teams lacked formal IPC accreditation or verification and rely on “short institutional visits and attended workshops” for training.

Timeliness

One respondent reported nSSI reports are produced every six months, whereas the other two respondents reported that nSSIS reports are produced annually. Two respondents indicated annual reports are provided to the general public. One respondent noted the report is made available to the MoH, and then is left to the discretion of the MoH whether the report is released to the public or not. Only one respondent stated that there is a governing body capable of responding to reports to induce change if needed; in that case the MoH was the capable governing body. Data transmission from the local to national level occurred at varying frequencies from monthly to annually.

Stability and impact of COVID-19

Two respondents reported that the effectiveness of the nSSIS program had never been re-evaluated, while one reported that the surveillance system was re-evaluated annually. All three respondents reported substantial impact on the nSSIS programs by the COVID-19 pandemic, with one program reporting a complete halt of all SSI surveillance activity, with the other two respondents noted that although the nSSIS programs remained intact, cessation of all elective surgical activity impeded reporting.

Discussion

Few LMICs report presence of a dedicated nSSIS program yet recommendations for establishing nSSIS programs have been registered by the WHO since 2011.⁸ Although it is tempting to attribute absence of these nSSIS programs to common scapegoats such as funding or political will, the reality is likely more nuanced. Even though funding limitations cannot be entirely disregarded or downplayed, solutions enabling sustainable implementation of these programs will likely need to be sequential and customized, rather than relying solely upon a large funding bolus or a regime change. To this end, we sought to identify successful components of existing LMICs nSSIS programs that may be utilized by SSI prevention champions in other LMICs settings as they develop their own program and identify pain points experienced by existing programs that can serve as a caution for others.

There were several notable strengths identified by respondents of the evaluated surveillance systems. First, use of local paper documentation and staggered data entry may be a realistic adaptation to reduced access to consistent electricity or internet. Although real-time reporting is attractive and ideal, it relies on a functioning power grid for the recorder, sender, and receiver of data. So even though data transmission may be more rapid with a completely electronic system, its feasibility may be limited in regions without dependable and consistent electricity or internet, or without access to adequate digital platforms. Similarly, although digital- or telephone-based patient reporting of SSIs is an attractive way to mitigate the low capture rate of post-discharge outcomes, it was interesting to note that all three functioning surveillance systems did not use these resources.^9–12 Further studies exploring how to increase utilization of patient-generated post-discharge health data in the LMIC context will be important.¹²

Second, the collected data fields were limited to the minimum amount of information needed to determine incidence. This simplicity reduced the burden of the data collectors but comes at the expense of risk-adjustment. Yet given the paucity of information about the incidence of SSIs in LMICs at the national level, this prioritization of simplicity over granularity to ensure accountability may be justified, particularly for countries without any existing nSSIS infrastructure. For fledgling nSSIS programs, emphasis may need to be placed on collecting the minimum amount of information required for determining disease incidence without overburdening surveillance teams, particularly during program inception. Perhaps most importantly is that these nSSIS programs were generally sustained through the COVID-19 pandemic. Although all respondents acknowledged that capacity was severely reduced, it is a testament to the passion and drive of the local and national IPC teams that the nSSIS programs survived such a globally disruptive event.

Notable opportunities for improvement and existing pain points were identified by the respondents. Commonalities included low outpatient data capture, inadequate coverage of healthcare centers within a nation, weak audit processes, difficulty in defining the denominator of number of surgical procedures, budget concerns, lack of integrated laboratory support, and absence of an easily accessible free SSI surveillance training program for healthcare workers.

Low outpatient data capture is a notoriously challenging problem for surveillance, SSI and otherwise, in LMICs settings.^9,13,14 Compensation for return visits can be costly when surveillance covers an entire nation. Without incentive, distracting patients from activities of daily living and their jobs to participate in medical follow-up can be challenging. Although many novel telephone- and digital-capture techniques have been developed, there appears to still be a need for novel strategies to improve capture or encourage adoption of existing methods.^10,11,13,15

Another notable challenge was the low rate of coverage of health facilities within the country. If only a small fraction of a country's health facilities report data, understanding the true burden of SSIs nationally becomes compromised. Notably, all respondents reported that while national reporting is “mandatory,” there are few, if any, financial incentives to participate and little downside from a facility standpoint for not participating. Working with political leadership to strengthen incentives to participate in the nSSIS program may be one way to help expand national coverage of a program, particularly given the costly burden of these infections in LMICs settings.^16,17 Marrying nSSIS reporting to WHO, United Nations, or national healthcare reimbursement could be one manner to encourage this commitment from national political leaders. Combined with political will and funding, developing and implementing nSSIS within a Disease Surveillance Informatics Optimization and Simulation (DIOS) framework may be particularly advantageous in lower resource settings.¹⁸ For all three respondents, the nSSIS programs were components of the national IPC programs. Leveraging existing surveillance infrastructure available within the IPC program may help ensure sustainability of a nSSIS program through shared resources and training and limit parallel data collection systems. Aligning nSSIS program goals with IPC program goal may help harmonize national efforts, particularly as countries try to scale up access to surgical care.

Finally, a common opportunity was the lack of standardized SSI surveillance training for healthcare workers and infection preventionists in LMICs. Notably, there is an increasing wealth of free, digital, self-paced training available for infection preventionists and healthcare providers in high income settings.¹⁹ There is also an online module produced by the WHO covering SSIs, the interconnectedness of SSI prevention and an IPC program, and monitoring SSIs within a LMICs local context.²⁰ Although these are important resources, there remains a perceived deficit of information about how to take local SSI surveillance data and integrate it within a broader nSSIS program at the national level. This unmet need could represent an opportunity for a relatively low-cost collaboration between international health organizations such as the WHO, medical societies, LMICs infection preventionists and physician and surgeon champions, and nSSIS participants in higher resource settings. Such a digital, online product may help alleviate some of the training gap currently reported from LMICs respondents.

There are several limitations to this study. First, this was a survey performed during the COVID-19 pandemic, which placed constraints on respondents' time and prohibited on-the-ground confirmation of reported findings. Respondents were approached by two authors at least three times over two-year period to maximize capture but competing priorities for respondents could have led to less comprehensive responses. We attempted to mitigate this through follow-up clarification of questions. Second, as with the first exploratory survey performed, there is likely selection bias among persons responding to the survey. Although we were encouraged that three of the five respondents initially reporting presence of a nSSIS program were willing and able to fill out our long form survey, the low number of respondents overall could limit broader applicability and relevance. Third, despite the pre-themed data collection, there was considerable heterogeneity in the responses reported limiting our ability to develop internal or external validity. Notably, despite a plurality of respondents being from the Latin American and Caribbean regions in our initial survey, we did not have any respondents from these countries in our follow-up survey. This could further limit broader applicability of our findings.

Our findings are summaries of the responses from one individual per country. Addition of more respondents per country could enable triangulation of responses which might help ensure reported data is as representative of the true state as possible. Finally, no surveillance system is perfect and nSSISs in high-resource settings have notable weaknesses.²¹ Our goal was not to contrast systems in LMICs to a given system in a high-income country, but to an ideal state to which all surveillance systems could be compared.

Conclusions

National surgical site infection surveillance programs remain an essential component of a country's ability to ensure surgery is performed safely. Common useful components of existing nSSIS in LMICs included batched digital transmission using paper data storage locally and prioritizing sparse and simple data collection over high granularity to improve data capture. Notable opportunities included low outpatient data capture, modest coverage of all health care facilities in a country, and a paucity of existing easy-to-access resources available to infection preventionists, surgeons, physicians and other healthcare providers interested in implementing and integrating a national surgical site infection surveillance program. Further collaboration between international medical organizations and healthcare leaders from LMICs should be undertaken to address these opportunities.

Footnotes

Acknowledgments

The authors would like to thank all of the respondents who participated in this survey.

Authors' Contributions

Data acquisition: Forrester, Bekele, Stefan, Tshokey, Berndtson, Beyene, Sayer, Chou, Valenzuela, Rickard. Data analysis: Forrester, Berndtson, Beyene, Sayer, Valenzuela, Rickard. Manuscript preparation: Forrester, Bekele, Stefan, Tshokey, Berndtson, Beyene, Sayer, Valenzuela, Rickard.

Funding Information

No financial or material support was received for this work product.

Author Disclosure Statement

Dr. Forrester received Surgical Infection Society Junior Faculty Award and has received unrestricted research funding from Varian (https://clinicaltrials.gov/ct2/show/NCT04482582 ) and Pacira () for investigator-initiated trials. These do not lead to conflicts of interest for this work product. No other authors have disclosures or conflicts of interest to report.

Supplementary Material

References

Forrester

, Berndtson

, Santorelli

, et al. Survey of national surgical site infection surveillance programs in low- and middle-income countries. Surg Infect, 2020; 21(7):621–625; doi: 10.1089/sur.2020.053

Rasa

, Kilpatrick

. Implementation of World Health Organization Guidelines in the prevention of surgical site infection in low- and middle-income countries: What we know and do not know. Surg Infect, 2020; 21(7):592–598; doi: 10.1089/sur.2020.163

Abbas

, de Kraker

MEA

, Aghayev

, et al. Impact of participation in a surgical site infection surveillance network: results from a large international cohort study. J Hosp Infect. 2019; 102(3):267–276; doi: 10.1016/j.jhin.2018.12.003

Rickard

, Beilman

, Forrester

, et al. Surgical infections in low- and middle-income countries: A global assessment of the burden and management needs. Surg Infect, 2020; 21(6):478–494; doi: 10.1089/sur.2019.142

German

, Lee

, Horan

, et al. Updated guidelines for evaluating public health surveillance systems: Recommendations from the Guidelines Working Group. MMWR Recomm Rep, 2001; 50(Rr-13):1–35; quiz CE31–37.

Buehler

, Hopkins

, Overhage

, et al. Framework for evaluating public health surveillance systems for early detection of outbreaks: recommendations from the CDC Working Group. MMWR Recomm Rep, 2004; 53(Rr-5):1–11.

National Healthcare Safety Network. Surgical Site Infection Event (SSI). Centers for Disease Control and Prevention; 2022. Available from: https://www.cdc.gov/nhsn/PDFs/pscManual/9pscSSIcurrent.pdf?agree=yes&next=Accept [Last accessed: September 27, 2022].

Allegranzi

, Bagheri Nejad

, Combescure

, et al. Burden of endemic health-care–associated infection in developing countries: Systematic review and meta-analysis. Lancet, 2011; 377(9761):228–241; doi: 10.1016/S0140-6736(10)61458-4

Pathak

, Sharma

, et al. Feasibility of a mobile phone-based surveillance for surgical site infections in rural India. Telemed J E Health, 2015; 21(11):946–949; doi: 10.1089/tmj.2014.0199

10.

Nguhuni

, De Nardo

, Gentilotti

, et al. Reliability and validity of using telephone calls for post-discharge surveillance of surgical site infection following caesarean section at a tertiary hospital in Tanzania. Antimicrob Resist Infect Control, 2017; 6(1):43; doi: 10.1186/s13756-017-0205-0

11.

Westercamp

, Barrie

, Conteh

, et al. Feasible surgical site infection surveillance in resource-limited settings: A pilot in Sierra Leone. Infect Control Hosp Epidemiol, 2020; 41(1_suppl):s38–s38; doi: 10.1017/ice.2020.517

12.

Evans

. Executive summary of the Assessing Surgical Site Infection Surveillance Technologies (ASSIST) Project. Surg Infect, 2019; 20(7):527–529; doi: 10.1089/sur.2019.171

13.

Sandberg

CEJ

, Knight

, Qureshi

, et al. Using telemedicine to diagnose surgical site infections in low- and middle-income countries: Systematic review. JMIR Mhealth Uhealth, 2019; 7(8):e13309; doi: 10.2196/13309

14.

Mutale

, Chintu

, Amoroso

, et al. Improving health information systems for decision making across five sub-Saharan African countries: Implementation strategies from the African Health Initiative. BMC Health Serv Res, 2013; 13(2):S9; doi: 10.1186/1472-6963-13-S2-S9

15.

Mehtar

, Wanyoro

, Ogunsola

, et al. Implementation of surgical site infection surveillance in low- and middle-income countries: A position statement for the International Society for Infectious Diseases. Int J Infect Dis, 2020; 100:123–131; doi: 10.1016/j.ijid.2020.07.021

16.

Graf

, Ott

, Vonberg

, et al. Surgical site infections—Economic consequences for the health care system. Langenbecks Arch Surg, 2011; 396(4):453–459; doi: 10.1007/s00423-011-0772-0

17.

Monahan

, Jowett

, Pinkney

, et al. Surgical site infection and costs in low- and middle-income countries: A systematic review of the economic burden. PLoS One, 2020; 15(6):e0232960; doi: 10.1371/journal.pone.0232960

18.

Cheng

, Collender

, Heaney

, et al. The DIOS framework for optimizing infectious disease surveillance: Numerical methods for simulation and multi-objective optimization of surveillance network architectures. PLOS Comput Biol, 2020; 16(12):e1008477; doi: 10.1371/journal.pcbi.1008477

19.

Centers for Disease Control and Prevention. SSI Training. National Healthcare Safety Network (NHSN) Training Web site. Available from: https://www.cdc.gov/nhsn/training/patient-safety-component/ssi.html [Last accessed: August 23, 2022].

20.

World Health Organization. Surgical Site Infections. Available from: https://openwho.org/courses/IPC-SSI-EN [Last accessed: August 23, 2022].

21.

, Ko

, Hall

, et al. A comparison of 2 surgical site infection monitoring systems. JAMA Surg, 2015; 150(1):51–57; doi: 10.1001/jamasurg.2014.2891

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.05 MB

0.00 MB