Introduction
The capacity to diagnose bacterial co-infections in patients with coronavirus disease 2019 (COVID-19) is limited by laboratory capacity, especially in low- and middle-income countries (LMICs) where access to microbiology is sparse. The large caseload of COVID-19 has resulted in global concerns about increasing empiric antibiotic usage and potential setbacks for antimicrobial stewardship (AMS) programs. This is particularly acute in low-resource settings without access to extensive microbiological testing. There is a real risk that new waves of COVID-19 may drive an increase in antimicrobial resistance, and there is a need for tools to guide optimal antimicrobial prescribing and stewardship. Reference Ming, Myall and Hernandez1
Host inflammatory biomarkers, such as procalcitonin (PCT) and C-reactive protein (CRP), have been proposed as possible indicators for distinguishing between viral and bacterial infections. Reference Lamrous, Repetto and Depp2–Reference Wolfisberg, Gregoriano and Schuetz4 Serum PCT levels in healthy individuals are usually <0.05 ng/mL; in most bacterial infections, the concentration increases in proportion with the severity of the illness. Reference Samsudin and Vasikaran5,Reference Cleland and Eranki6 In most viral infections, increased interferon gamma production inhibits PCT synthesis, leading to relative bacterial specificity of PCT. Reference Malinverni, Lazzaroni and Nunez7 However, there are clinical situations that may lower this specificity, including patients on medications that stimulate cytokine release, chronic kidney disease, major surgery, or severe trauma. Reference Samsudin and Vasikaran5,Reference Omer, Abuthiyab, Zaid, Alkanani, Abualnaja and Khan8 Normal CRP levels in most healthy adults are usually <10.0 mg/L. There are both acute and chronic conditions and infectious and noninfectious etiologies for an elevated CRP level. However, CRP levels rise and fall rapidly with the introduction and removal of inflammatory stimuli. These and other factors mandate the interpretation of biomarkers within the context of other laboratory and clinical findings. Reference Calderon, Li and Bazo-Alvarez9,Reference Schuetz, Bretscher, Bernasconi and Mueller10
Prior to the pandemic, the Food and Drug Administration in the United States had advised on cut-off values for PCT-guided antibiotic use in lower respiratory tract infections, as well as international consensus on the use of PCT in combination with clinical patient assessment for AMS algorithms. Reference Schuetz, Bretscher, Bernasconi and Mueller10–12 During the COVID-19 pandemic, several guidelines were published suggesting the use of biomarkers for AMS purposes—the United Kingdom (UK) first published the NICE rapid guidance NG173 on May 1, 2020. 13 However, whether biomarkers could be used as an indicator of secondary bacterial infection and need for antibiotics in severe acute respiratory coronavirus virus 2 (SARS-CoV-2) positive patients is a more specific question that needs to be answered, especially for LMICs.
Therefore, the primary objectives of this study were to assess the usefulness of CRP and PCT in the diagnosis of bacterial co-infections in COVID-19 and if their incorporation in AMS programs is safe and useful, stratified by severity of disease as level of care, intensive care unit (ICU) or non-ICU. Our secondary objectives were to identify cut-off values for antibiotic decision-making and identify reported results from LMICs.
Methods
This was a scoping review of published literature, adhering to the PRISMA statement for Systematic Reviews and Meta-analyses Extension for Scoping Reviews guidelines. Reference Tricco, Lillie and Zarin14 Studies published from January 2020 onward in all languages were considered eligible for screening. The following key terms were included: “COVID and/or SARS-CoV-2,” “antibiotic stewardship” or “antimicrobial stewardship,” “bacterial co-infection,” and biomarkers or procalcitonin/PCT or C-reactive protein/CRP. The last search was performed in January 2024. The PubMed, Scopus, EMBASE, and Web of Science databases were used to identify relevant literature. Search histories were uploaded in Covidence, a web-based collaboration software platform that streamlines the production of systematic and other literature reviews. 15
Initial abstract review and full text screening was performed in duplicate by AW and ER, with conflicts resolved by TOJ. Extraction of data was performed in duplicate by any 2 of the authors (AW, ER, MK, TOJ), with a third performing a consensus check. The reference lists of key systematic review articles were also manually searched for studies not identified through electronic searches. Reference Kyriazopoulou and Giamarellos-Bourboulis3,Reference Wolfisberg, Gregoriano and Schuetz4,Reference Omer, Abuthiyab, Zaid, Alkanani, Abualnaja and Khan8
Studies that did not address the diagnosis of bacterial co-infections in COVID-19 specifically, or a stewardship program, were excluded. Additionally, studies that only explored the use of biomarkers as predictors of severity, clinical outcomes, or length of stay were excluded.
Results
Figure 1 displays the flow diagram describing the article selection process. Initially, 2,819 references were imported for screening with an additional 17 references from citation searching of key review articles. Once titles and abstracts were screened, 145 articles were evaluated for inclusion, leading to 59 studies being included in the review.
Of the 59 studies selected, 48 were conducted in high-income countries (HICs) with 14 studies conducted in the United States and 11 conducted in the UK. Seven studies were conducted in upper middle-income countries (UMICs); 5 studies were from China, and 1 was a multicenter study conducted concurrently in several HICs and UMICs. Three studies were conducted in LMICs: 1 each from India, Nepal, and Pakistan (Table 1).
–, not recorded; BC, blood culture; BAL, bronchoalveolar lavage; CO, community onset; CRP, C-reactive protein; HAI, hospital-associated infection; HIC, high-income country; HO, hospital-onset; ICU, intensive care unit; LMIC, low-middle-income country; PCT, procalcitonin; RC, respiratory cultures; UK, United Kingdom; UMIC, upper middle-income country; USA, United States of America; VAP, ventilator-associated pneumonia.
Most studies started and ended in 2020, during the first 2 waves of the pandemic. Several studies ended in 2021, 2 studies reported from 2022, and for 1 study, the study period was not specified. Several studies spanned multiple years. Although the majority were retrospective observational studies, there were 8 prospective studies and 1 randomized controlled trial (RCT).
The study population varied from a minimum of 49 to a maximum of 4,635 patients. One study specifically looked at the pediatric population, while the majority excluded patients <18 years old. Fifteen studies were specifically reported on patients admitted to an ICU. Ten studies investigated only respiratory co-infections, while most studies investigated both respiratory and non-respiratory co-infections.
The prevalence of microbiologically confirmed secondary bacterial infection varied from 1% to 60.6% with 5 studies not reporting secondary bacterial infections (Table 1).
Overall, for mild cases of COVID-19, most studies concluded positively for the use of biomarkers to rule out bacterial co-infections but should be interpreted with caution or in a multimodal approach with clinical assessment. However, most studies involving patients with severe COVID-19 concluded negatively on the use of PCT and bacterial co-infections; 2 studies Reference Sathitakorn, Jantarathaneewat and Weber64,Reference Tanzarella, Vargas and Menghini66 described the use of CRP and/or PCT with an algorithm score, and 1 study Reference Cidade, Coelho and Póvoa28 investigated the kinetics of biomarkers for ICU-acquired infections.
PCT results
There were 53 studies that assessed PCT levels and their relation with bacterial co-infections; 29 studies measured PCT with CRP levels, and 24 measured only PCT. Twenty studies reported negative predictive values (NPV), positive predictive values (PPV), and/or sensitivity and specificity for bacteria co-infections according to the chosen PCT cut-off values (Table 2). Reference Malinverni, Lazzaroni and Nunez7,Reference Atallah, Warren and Roberts19,Reference Azijli, Minderhoud, de Gans, Lieveld and Nanayakkara20,Reference Campani, Talamonti and Dall’Ara23–Reference Ceccarelli, Alessandri and Migliara25,Reference Cowman, Rossi and Gendlina31,Reference Dolci, Robbiano and Aloisio32,Reference Galli, Bindo and Motos36,Reference He, Liu and Jiang40,Reference Houghton, Moore and Williams44,Reference May, Chang and Dietz51,Reference Moreno-García, Puerta-Alcalde and Letona54,Reference Nazerian, Gagliano, Suardi, Fanelli, Rossolini and Grifoni56,Reference Ng, Ong and Loo57,Reference Pink, Raupach and Fuge60,Reference Relph, Russell and Fairfield61,Reference van Berkel, Kox, Frenzel, Pickkers and Schouten67–Reference Vaughn, Gandhi and Petty69
bPNA, bacterial pneumonia; BSI, bloodstream infection; CO, community onset.
a PCT cut-off >0.8 ng/mL.
b PCT cut-off >2.5 ng/mL.
* No units reported.
PCT cut-off values varied from 0.1 ng/ml up to 2 ng/ml; in 10 studies, multiple cut-off values were considered, where most studies considered 0.25 ng/mL as the lower cut-off value and 0.5 ng/mL as the upper cut-off value. Two studies established cut-off values by using receiver operating curves (ROC) to determine a sensitivity of 80%. Reference Campani, Talamonti and Dall’Ara23,Reference Galli, Bindo and Motos36 In general, studies with lower cut-off values reported higher NPVs, and studies with higher cut-off values reported higher PPVs for bacterial co-infections. NPVs ranged from 58.2% to 100% using ≤0.25 ng/mL as the cut-off. PPVs ranged from 3.5% using 0.12 ng/mL to 85.5% using 0.25 ng/mL as cut-offs. There was a varied range of results for sensitivity and specificity for detecting bacterial co-infections across the board with no obvious trends (Table 2).
CRP results
Thirty-four studies measured CRP levels in COVID-19 patients; 4 measured CRP levels only, while 29 measured both CRP and PCT. Reported cut-off values ranged from 65mg/L to 312.5 mg/L; 1 study did not report a cut-off value but did report a sensitivity result Reference He, Liu and Jiang40 , and 1 study provided cut-off values for the initial result and 1 for the peak result Reference Dolci, Robbiano and Aloisio32 . Two studies determined cut-off values from using ROC to determine a sensitivity of 80%. Reference Campani, Talamonti and Dall’Ara23,Reference Galli, Bindo and Motos36
Antimicrobial stewardship (AMS)
Of the 59 studies reviewed, 8 studies reported clear objectives around AMS in their design and were further analyzed (Table 3). Reference Calderon, Li and Bazo-Alvarez9,Reference Anderson, Bennett, Aragon, Kennedy and Boyd17,Reference Fartoukh, Nseir and Mégarbane34,Reference Fratoni, Kois, Colmerauer, Linder, Nicolau and Kuti35,Reference Moore, Wilde, Bohn, Song and Schulz53,Reference Peters, Williams and Un58,Reference Sathitakorn, Jantarathaneewat and Weber64,Reference Williams, Mair and de Silva70 Five were retrospective studies and conducted in HICs (UK, USA); Reference Calderon, Li and Bazo-Alvarez9,Reference Fratoni, Kois, Colmerauer, Linder, Nicolau and Kuti35,Reference Moore, Wilde, Bohn, Song and Schulz53,Reference Peters, Williams and Un58,Reference Williams, Mair and de Silva70 there was 1 prospective study conducted in a UMIC (Thailand), a before-and-after observational study in a HIC (USA), Reference Anderson, Bennett, Aragon, Kennedy and Boyd17 and an RCT from a HIC (France) Reference Fartoukh, Nseir and Mégarbane34 . All studies used PCT as a biomarker, with a cut-off of 0.25 ng/mL, except in 2 studies where there were categories of cut-offs (<0.25 ng/mL, ≥0.25–<0.5ng/mL, ≥0.5ng/mL), Reference Fartoukh, Nseir and Mégarbane34,Reference Peters, Williams and Un58 and 1 study used 0.5 μg/L as the cut-off. Reference Sathitakorn, Jantarathaneewat and Weber64 Two studies only included patients admitted in ICU, 2 studies had both ICU and non-ICU patients, while the other 4 studies only included patients admitted in general wards.
AM, antimicrobial; AMS, antimicrobial stewardship; COVID-19, coronavirus disease 2019; DDD, defined daily dosage; LoS, length of stay; ROM, ratios of means.
Two of 8 studies directly compared measures of antimicrobial use in a group that incorporated PCT guidance versus a group without PCT measurements. Reference Calderon, Li and Bazo-Alvarez9,Reference Fartoukh, Nseir and Mégarbane34 All 4 studies that compared defined daily doses (DDD) of antimicrobial treatment observed a significant reduction in the PCT group versus the group without PCT guidance Reference Calderon, Li and Bazo-Alvarez9,Reference Anderson, Bennett, Aragon, Kennedy and Boyd17,Reference Peters, Williams and Un58,Reference Williams, Mair and de Silva70 . Six studies compared the length of antimicrobial treatment in groups with and without PCT guidance; 4 of these demonstrated a reduction when PCT was used, and 2 did not detect a difference between groups. Reference Calderon, Li and Bazo-Alvarez9,Reference Anderson, Bennett, Aragon, Kennedy and Boyd17,Reference Fartoukh, Nseir and Mégarbane34,Reference Fratoni, Kois, Colmerauer, Linder, Nicolau and Kuti35,Reference Sathitakorn, Jantarathaneewat and Weber64,Reference Williams, Mair and de Silva70
Similarly, different secondary measures of safety were used in comparative studies. In 6 studies reporting on mortality rate, no adverse effect of PCT-guided AMS was detected, Reference Anderson, Bennett, Aragon, Kennedy and Boyd17,Reference Fartoukh, Nseir and Mégarbane34,Reference Fratoni, Kois, Colmerauer, Linder, Nicolau and Kuti35,Reference Sathitakorn, Jantarathaneewat and Weber64 and a reduction was seen in 2 studies. Reference Calderon, Li and Bazo-Alvarez9,Reference Williams, Mair and de Silva70 Of the 7 studies that measured the length of stay (LoS), Reference Calderon, Li and Bazo-Alvarez9,Reference Anderson, Bennett, Aragon, Kennedy and Boyd17,Reference Fartoukh, Nseir and Mégarbane34,Reference Fratoni, Kois, Colmerauer, Linder, Nicolau and Kuti35,Reference Moore, Wilde, Bohn, Song and Schulz53,Reference Sathitakorn, Jantarathaneewat and Weber64,Reference Williams, Mair and de Silva70 2 observed a reduction in the PCT group, Reference Sathitakorn, Jantarathaneewat and Weber64,Reference Williams, Mair and de Silva70 and no difference was detected in the remaining studies. Four studies measured Clostridioides difficile infections, Reference Anderson, Bennett, Aragon, Kennedy and Boyd17,Reference Fartoukh, Nseir and Mégarbane34,Reference Fratoni, Kois, Colmerauer, Linder, Nicolau and Kuti35,Reference Williams, Mair and de Silva70 and 1 observed a nonsignificant reduction in incidence with PCT-guided AMS. Reference Fartoukh, Nseir and Mégarbane34
LMIC studies
Only 3 studies were reported from LMICs. Reference Basnet, Chand and Shrestha21,Reference Lukose, Kaur and Abraham49,Reference Nasir, Rehman and Omair55 All studies were retrospective descriptive studies and were performed at a teaching/university hospital.
The study from Nepal by Basnet et al Reference Basnet, Chand and Shrestha21 describes a cross-sectional study investigating the prevalence of uropathogenic Escherichia coli among COVID-19 patients admitted to tertiary care. Of the 49 COVID-19 patients with symptoms of a urinary tract infection, 3 had uropathogenic E. coli (6.1%) detected. The mean PCT levels were higher for co-infected patients than not (6.13 ng/mL vs 0.95 ng/mL, respectively). It is unknown if the patients were in ICU or had severe COVID-19, which may have affected the PCT levels.
The study from Pakistan by Nasir et al Reference Nasir, Rehman and Omair55 describes a retrospective case-control study of 50 COVID-19 patients with a confirmed bacterial infection matched to COVID-19 patients without bacterial co-infection. Patients were from both the ICU and normal medical wards. Almost ¾ of co-infections were hospital-acquired (72%), with the majority being hospital-acquired pneumonia. Compared to patients without an infection, there was no significant difference in CRP or PCT on logistic regression analysis. Although there were no significant results for these host biomarkers, the report highlights the need for AMS, as 64% (32/50) of patients without a confirmed infection received antibiotics.
The study from India by Lukose et al Reference Lukose, Kaur and Abraham49 evaluated the patterns and predictors of empirical antibiotic therapy in patients admitted for moderate and severe COVID-19. Elevated PCT [OR: 3.91 (95% CI, 1.66–9.16) (P = 0.001)] levels were identified as predictors for initiating empirical anti-bacterial therapy, but no specific cut-off values were identified.
Discussion
This scoping review provides an overview of where and how biomarkers were used throughout the first waves of the COVID-19 pandemic to assist with AMS efforts. Procalcitonin has the potential to help in diagnosing bacterial co-infections in patients with COVID-19; however, the predictive values (NPV/PPV) are inadequate for the tests to be used in isolation and results to be interpreted together with other clinical information.
Most identified studies considered PCT at 0.25 ng/mL as the cut-off value for withholding antibiotic prescriptions, with some studies using 0.5 ng/mL as a higher cut-off value—often studies within the ICU. This is similar to what was reported in a similar review from earlier in the pandemic; Omer et al Reference Omer, Abuthiyab, Zaid, Alkanani, Abualnaja and Khan8 reported that half of the studies used 0.5/0.55ng/mL and another third used 0.2/0.25 ng/mL. However, in a meta-analysis of 8 studies using a PCT cut-off of 0.5 ng/mL to distinguish between bacterial and viral CAP prior to the COVID-19 pandemic, Kamat et al Reference Kamat, Ramachandran, Eswaran, Guffey and Musher72 concluded that the sensitivity and specificity estimates are too low to confidently use this PCT cut-off in decision-making processes. Reference Schouten, De Waele and Lanckohr73
In this review, there were a limited number of studies evaluating CRP, with a wide range of cut-off values from the 5 studies using CRP alone. There was no consensus on cut-off values from the studies reporting CRP, and furthermore, there are several confounding issues with COVID-19, inflammation and CRP.
Interestingly, several studies propose the use of CRP and PCT in combination with other inflammatory markers and clinical scores. Reference He, Liu and Jiang40,Reference May, Chang and Dietz51,Reference Moreno-García, Puerta-Alcalde and Letona54 When using a clinical pulmonary infection score with a PCT cut-off of 0.5 ug/L in severely ill COVID-19 patients, Sathitakorn et al Reference Sathitakorn, Jantarathaneewat and Weber64 reported those with a negative score were less likely to have inappropriate antibiotics used, less likely to have inappropriate empirical antibiotic initiated, and more likely to have antibiotics discontinued at 72 hours. In their retrospective analyses, both Gianella and Tanzarella et al used the clinical findings to develop a predicative model for bacterial pneumonia diagnosis: Gianella et al in all COVID-19 patients and Tanzarella et al in severe COVID-19 patients. Reference Giannella, Rinaldi and Tesini38,Reference Tanzarella, Vargas and Menghini66 Both studies also include PCT (≥0.2 ng/mL) and WBC in their scores. Therefore algorithms with several biomarkers and clinical scores may overcome the limitations of individual biomarker interpretation.
Our search only identified 3 retrospective studies conducted in LMICs; all were reported from Asia, specifically in tertiary hospitals/teaching hospitals with better access to diagnostic facilities. Due to differing study populations, small study population sizes in 2 of the 3 studies, no clearly defined cut-off values, different conclusions, and no strong recommendations, there can be no overarching inferences made for the use of biomarkers for COVID-19 patients in LMICs. However, a recent review by Lamrous et al in non-COVID-19 LMIC contexts suggests that PCT is likely to be as reliable a clinical tool in LMICs as in HICs, particularly in respiratory tract infections, sepsis, and HIV/TB. Reference Lamrous, Repetto and Depp2 However, more studies are needed to reach a consensus regarding laboratory standards and cut-off values.
We identified a lack of representation from other geographical areas such as Africa and Latin America, where the different epidemiology of potential co-infections (malaria, dengue, etc.) on biomarkers behaviors in COVID-19 has not been reported. Although there are potential host and pathogen response differences for PCT and CRP in the presence of LMIC geographical specific endemic infections, this is unlikely to dramatically influence their dynamics in the context of COVID-19.
Overall, there were few studies that documented the direct integration of biomarkers into AMS programs and none from LMICs. From the 5 studies that specifically reported AMS outcomes in this review, there was an overall decrease in antibiotic consumption with no impact on the measures of safety reported for mild COVID-19 cases (Table 3). Thirteen of the 18 studies in the Omer et al review indicated positively the use of PCT for ruling out superimposed bacterial infection(s) and/or as an AMS tool, while in the Wolfisberg et al review found that for COVID-19 specifically, most studies reported reduced antibiotic use with no negative impacts on outcomes. Reference Wolfisberg, Gregoriano and Schuetz4,Reference Omer, Abuthiyab, Zaid, Alkanani, Abualnaja and Khan8 The MultiCoV RCT used a respiratory multiplex Polymerase Chain Reaction (PCR) panel and PCT algorithm to reduce antibiotic exposure in patients with severe confirmed COVID-19 pneumonia and reported no significant differences in serious adverse events or mortality rate between the PCR/PCT algorithm and conventional strategies. Reference Fartoukh, Nseir and Mégarbane34 Ultimately, the scarcity of articles in this review highlights the need for more trials and implementation research, particularly in the context of COVID-19 and low-resourced settings.
However, the best AMS algorithms are only as good as the compliance rate, with consistent education key. Reference Kyriazopoulou and Giamarellos-Bourboulis3,Reference Christensen, Haug, Berild, Bjørnholt and Jelsness-Jørgensen74 In an evaluation of an AMS program with PCT guidelines in the UK, Williams et al Reference Williams, Mair and de Silva70 found that one-third of patients in the negative PCT (≤0.25 ng/ml) group were on antibiotics 48 h after a COVID-19 diagnosis, compared to 84% of patients with a positive PCT (>0.25 ng/mL) result. In a qualitative study investigating hospital physicians’ experiences with using PCT in an AMS algorithm in Norway (prior to COVID-19), physicians reported a knowledge gap in usage, expressing uncertainty of usage and interpretation, with some clinicians describing experiences where PCT failed to indicate a bacterial infection and thereby increased their lack of confidence in PCT as an indicator. Reference Christensen, Haug, Berild, Bjørnholt and Jelsness-Jørgensen74 The transition from the evidence of biomarkers to the practice of using them within AMS programs needs to be explored further with implementation research.
There are limitations to this review considering the objectives of this study. First, we did not consider the interaction of immune modulators with biomarkers in COVID-19 patients. The use of dexamethasone, tocilizumab, or baricitinib may confound the interpretation of host inflammatory markers and thereby limit the diagnostic performance of biomarkers. Studies have concluded that in critically ill COVID-19 patients, CRP and PCT have shown rebound increases upon cessation of immunomodulator treatment, and as such, clinicians should assess basic clinical infection signs and cultures for diagnosis of secondary bacterial infections. Reference Kyriazopoulou and Giamarellos-Bourboulis3,Reference Kooistra, van Berkel and van Kempen75
Most studies were retrospective single-center studies, conducted during the first wave of COVID-19; most studies in this review were performed in 2020, particularly early/mid-2020, and before mass vaccination campaigns. Subsequent variants of SARS-CoV-2 and vaccination coverage have resulted in infections with different transmissibility, epidemiology, hospitalization, and mortality rates. Reference Geddes76
Most studies in this review were conducted in HICs with better laboratory capacity to aid the diagnosis of bacterial co-infection. Only 3 studies were performed in LMICs, and there was a lack of representation from Africa and Latin America, where there are different endemic diseases that may play a role in the dynamics of biomarkers. Reference Lamrous, Repetto and Depp2
Finally, although there was a larger proportion of studies that used 0.25 ng/mL as a PCT cut-off, there needs to be a clear consensus on biomarker cut-offs and what that cut-off determines—whether that be the prescription, the de-escalation, or the withdrawal of antimicrobial agents. Larger, multicenter studies need to be performed to provide clear evidence for this decision; the current BATCH and PEACH trials will hopefully add to the necessary evidence to make these decisions. Reference Euden, Pallmann and Grozeva77,Reference Schoenbuchner, Huang and Waldron78
Conclusion
In the context of non-ICU hospitalized COVID-19 cases in HMICs, a PCT cut-off value below 0.25 mg/L can be a useful tool to rule out bacterial co-infection, but the wide range of NPVs reported in this review suggests that PCT should be interpreted in the context of other clinical findings. However, from this review, there is too little data to be conclusive about the use of CRP in the same manner. AMS programs in the right clinical context can incorporate a PCT value of <0.25 mg/L as a cut-off for the administration of antibiotics in mild COVID-19 patients without concerns for adverse outcomes. Although non-COVID-19-specific evidence suggests that the use of PCT in this manner should be safe in LMICs, local scientific institutions, international research partnerships, and humanitarian organizations can play an essential role to pilot the use of PCT as an antibiotic stewardship tool in the COVID-19 context.
Author contributions
Anita Williams: conceptualization, methodology, data curation, formal analysis, writing—original draft, project administration; Ernestina Repetto: conceptualization, methodology, data curation, formal analysis, writing—original draft; Ishmael Lebbie: formal analysis, writing—review and editing; Mohamad Khalife: formal analysis, writing—review and editing; Tomas Ostergaard Jensen: conceptualization, methodology, data curation, formal analysis, writing—original draft, supervision.
Financial support
This work was supported by routine program funding of Médecins Sans Frontières (MSF) Luxembourg Operational Research Unit (LuxOR) and Middle East Medical Unit (MEMU).
Competing interests
All authors report no conflicts of interest relevant to this article.