Clinical Characteristics and Factors Associated with Long COVID in Zambia, August 2020 to January 2023: A Mixed Methods Design

Clinical Characteristics and Factors Associated with Long COVID in Zambia, August 2020 to January 2023: A Mixed Methods Design | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Clinical Characteristics and Factors Associated with Long COVID in Zambia, August 2020 to January 2023: A Mixed Methods Design View ORCID Profile Warren Malambo , View ORCID Profile Duncan Chanda , View ORCID Profile Lily Besa , Daniella Engamba , Linos Mwiinga , Mundia Mwitumwa , Peter Matibula , Neil Naik , Suilanji Sivile , View ORCID Profile Simon Agolory , View ORCID Profile Andrew Auld , Lloyd Mulenga , Jonas Z. Hines , Sombo Fwoloshi doi: https://doi.org/10.1101/2024.01.17.24301423 Warren Malambo 1 U.S. Centers for Disease Control and Prevention, Division of Global HIV/TB , Lusaka, Zambia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Warren Malambo For correspondence: ykh1{at}cdc.gov Duncan Chanda 2 University Teaching Hospital Adult and Emergency Hospital, Department of Internal Medicine , Lusaka, Zambia 3 Ministry of Health , Lusaka, Zambia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Duncan Chanda Lily Besa 3 Ministry of Health , Lusaka, Zambia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Lily Besa Daniella Engamba 2 University Teaching Hospital Adult and Emergency Hospital, Department of Internal Medicine , Lusaka, Zambia 3 Ministry of Health , Lusaka, Zambia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Linos Mwiinga 1 U.S. Centers for Disease Control and Prevention, Division of Global HIV/TB , Lusaka, Zambia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Mundia Mwitumwa 2 University Teaching Hospital Adult and Emergency Hospital, Department of Internal Medicine , Lusaka, Zambia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Peter Matibula 2 University Teaching Hospital Adult and Emergency Hospital, Department of Internal Medicine , Lusaka, Zambia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Neil Naik 2 University Teaching Hospital Adult and Emergency Hospital, Department of Internal Medicine , Lusaka, Zambia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Suilanji Sivile 2 University Teaching Hospital Adult and Emergency Hospital, Department of Internal Medicine , Lusaka, Zambia 3 Ministry of Health , Lusaka, Zambia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Simon Agolory 1 U.S. Centers for Disease Control and Prevention, Division of Global HIV/TB , Lusaka, Zambia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Simon Agolory Andrew Auld 1 U.S. Centers for Disease Control and Prevention, Division of Global HIV/TB , Lusaka, Zambia Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Andrew Auld Lloyd Mulenga 3 Ministry of Health , Lusaka, Zambia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jonas Z. Hines 1 U.S. Centers for Disease Control and Prevention, Division of Global HIV/TB , Lusaka, Zambia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sombo Fwoloshi 2 University Teaching Hospital Adult and Emergency Hospital, Department of Internal Medicine , Lusaka, Zambia 3 Ministry of Health , Lusaka, Zambia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract Introduction A number of seroprevalence studies in Zambia document the extent of spread of SARS-CoV-2, yet few have examined signs, symptoms and conditions that continue or develop after acute COVID-19 infection (long COVID). This is an important gap given the estimated prevalence of long COVID in other countries. We sought to examine characteristics of post-acute COVID-19 (PAC-19) clinics patients in Zambia and assess factors associated with long COVID at first visit to a PAC-19 clinic and longitudinally among a cohort of patients. Methods Long COVID was defined, initially in the Zambia PAC-19 clinical guidelines, as new, relapsing, or persistent symptoms lasting >4 weeks after an initial SARS-CoV-2 infection. Severe COVID-19 was defined as COVID-19 episode that required supplemental oxygen therapy, intensive care unit stay or treatment with steroids/remdesivir. We performed a cross-sectional and longitudinal analysis of PAC-19 clinic patients from August 2020 to January 2023 using logistic and mixed effects regression models and considered statistical significance at p<0.05. Results In total, 1,359 patients attended PAC-19 clinics of whom 548 (40.3%) with ≥2 visits were included in the longitudinal analysis. Patients’ median age was 53 (interquartile range [IQR]: 41-63) years, 919 (67.6%) were hospitalized for acute COVID-19, and of whom 686 (74.6%) had severe COVID-19. Patients with hospital length of stay ≥15 days (adjusted odds ratio [aOR]: 5.37; 95% confidence interval [95% CI]: 2.99-10.0), severe illness (aOR: 3.22; 95% CI: 1.68-6.73), and comorbidities (aOR:1.50; 95% CI: 1.02-2.21) had significantly higher likelihood of long COVID. Longitudinally, long COVID prevalence significantly (p<0.001) declined from 75.4% at the first PAC-19 visit to 26.0% by the fifth visit. The median follow-up time was 7 (IQR: 4-12) weeks. Conclusion Long COVID symptoms were common among patient presenting for care in PAC-19 clinics in Zambia, but most recovered within ∼2 months. Despite potentially substantial morbidity due to long COVID, few patients overall with COVID-19 attended a PAC-19 clinic. Scaling up PAC-19 services and integrating into routine clinical care could improve access by patients. Introduction Since the identification of the first SARS-CoV-2 infections in December 2019, the Coronavirus disease 2019 (COVID-19) has become a major public health problem. Its morbidity and mortality dramatically increased across countries and regions leading to its classification as a pandemic [ 1 ]. As of February 2024, the World Health Organization (WHO) had reported over 774 million cumulative COVID-19 cases and over 7 million cumulative COVID-19 deaths globally [ 2 ]. In the Africa region alone, over 9.5 million cumulative COVID-19 cases and over 175 thousand COVID-19 deaths were reported for the same time period. People infected with SARS-CoV-2 commonly develop symptoms within 4-5 days following exposure although others may be asymptomatic [ 3 ]. Acute COVID-19 (within 4 weeks from the initial SARS-CoV-2 infection) presents with as a multi-system cluster of symptoms, i.e., general, cardiovascular, pulmonary, gastrointestinal, neurologic, musculoskeletal, and ear, nose, and throat. Recovery from COVID-19 for most patients occurs within 7-10 days after symptoms onset but could take weeks to months in some patients [ 4 – 7 ]. Previous epidemics such the 2003 severe acute respiratory syndrome (SARS) and the 2012 Saudi Arabia Middle East respiratory syndrome coronavirus (MERS-CoV) had patients who presented with persistent symptoms post-acute infection [ 8 – 11 ]. Their symptoms included fatigue, decreased quality of life, shortness of breath and behavior health problems that impacted on their health-related quality of life. Symptoms and conditions that continue or develop after acute COVID-19 infection are variably named (post-acute COVID-19, post-acute sequelae of SARS-CoV-2 infection, post-COVID conditions, long-haul COVID, post-COVID conditions, long-term effects of COVID and chronic COVID) but are also referred to as long COVID [ 6 , 12 ]. Commonly reported long COVID symptoms include fatigue, fever, cough, dizziness, brain fog, and myalgia although symptoms are varied and potentially have overlapping etiologies [ 13 – 15 ]. Long COVID is thus a syndrome characterized by persistent, new, relapsing or delayed SAR-CoV-2 symptoms ≥12 weeks beyond onset of the acute episode [ 12 , 16 – 18 ], and can have a protracted path to recovery that impacts on quality of life, earnings and health care costs [ 19 – 21 ]. As much as 77 million people around the world could be estimated to have long COVID, based on a conservative estimated prevalence of 10% of reported number of infected people [ 2 , 22 ]; the actual number may likely be much higher given undocumented cases due to limited testing capacity. Among acute-COVID-19 outpatient cases, the prevalence of long COVID is estimated at 10-30%; 50-70% of hospitalized cases and 10-12% of vaccinated cases [ 22 – 27 ]. For example, a study of the burden, causation, and particularities of long COVID in 7 African countries estimated a pooled long COVID prevalence of 41% [ 28 ]. Long COVID is associated with increasing age, comorbidities, hospitalization for acute COVID-19, severe COVID-19, and vaccination status [ 29 – 31 ]. Vaccination against SARS-CoV-2 is, however, associated with reduced likelihood of severe COVID-19 and long COVID. There’s growing evidence on long COVID from countries in Africa [ 28 , 32 – 34 ]. Disease severity and admission to the intensive care unit during acute COVID-19, for example, were found to be associated with long COVID in Nigeria and South Africa [ 35 , 36 ]. Scoping studies on long COVID in Africa found comorbidities and age >40 years to be associated factors [ 33 , 37 ]. In Zambia, 17% of persons with acute COVID-19 in July 2020 were found to be experiencing symptoms ∼2 months later [ 38 ]. Zambia’s reported COVID-19 cases are, however, likely an underestimate given limited testing capacity, asymptomatic infections, and mild clinically ill cases who may not have come to the attention of the health system [ 39 – 41 ]. While a number of seroprevalence studies in Zambia document the extent of spread of SARS-CoV-2, few have examined longer term outcomes such as long COVID [ 36 , 39 , 41 – 45 ]. This is an important gap given the estimated prevalence of long COVID and extent of SARS-CoV-2 transmission in other countries in Africa. In this study, we examined the characteristics of patients presenting for care in specialized post-acute COVID-19 (PAC-19) clinics in Zambia and assessed factors associated with long COVID at first visit to a PAC-19 clinic and longitudinally among a cohort of patients with ≥2 PAC-19 clinic visits. Methods Study setting Beginning August 2020, the Zambia Ministry of Health set up 13 specialized PAC-19 clinics to care for people following SARS-CoV-2 infection, initially at the two national referral hospitals in Lusaka city, the capital of Zambia, and subsequently at 11 other major hospitals across all 10 provinces of Zambia. Study participants Per national PAC-19 clinical guidelines, patients diagnosed with SARS-CoV-2 infection presented in PAC-19 clinics for follow-up care after discharge from hospital admission or outpatient episodic [ 46 ]. At the first PAC-19 clinic visit, patients’ demographics, medical history, comorbidities, and current symptoms were recorded on a standardized paper form. Physical examinations and laboratory investigations were conducted based on patient’s medical history as required. Patients’ ability to perform activities, as part of examination of their functional and mental health status, were also evaluated. Further clinical appointments of up to 5 review visits were at the clinicians’ discretion. Symptoms were assessed by clinicians at each PAC-19 clinic visit on review of systems: general, cardiovascular, pulmonary, urinary, neurologic, musculoskeletal, ear, nose, and throat (ENT), mental health concerns, depression, anxiety, and dermatologic. Pre-existing comorbidities (hypertension, diabetes, cardiovascular disease, cancer, chronic lung disease, kidney disease, or liver disease, immunosuppression, obesity, HIV and TB) were documented. Patients requiring further specialist care were referred to various units including physiotherapy, cardiology, endocrinology, nephrology, psychiatry, and pulmonology. Anonymized data from patients standardized clinical paper forms were routinely abstracted into an electronic database (REDCap v11.0.3); which was accessed on 5 th January 2023 and analyzed for this study. Study design We implemented a mixed methods design to assess for factors associated with long COVID at first visit to a PAC-19 clinic and longitudinally across review visits. First, we performed a cross-sectional analysis of all PAC-19 clinic patients with data entered in the REDCap electronic databases from August 5, 2020, through to January 26, 2023. We then did a longitudinal sub-analysis of patients with ≥2 PAC-19 clinic review visits. The longitudinal sub-analysis data structure included repeated observations of long COVID symptoms and patient-level characteristics. Demographic and clinical characteristics of patients included time-invariant covariates sex, age (patients repeatedly observed for <1 year), presence of newly diagnosed medical conditions, presence of pre-existing comorbidities, and acute COVID-19 episode details. Time-variant covariates included COVID-19 vaccination status and referral to specialist services. Study variables and definitions Long COVID was defined, initially in the Zambia post-acute COVID-19 guidelines, as new, relapsing or persistent COVID-19 symptoms that lasted greater than 4 weeks after the initial SARS-CoV-2 infection [ 46 , 47 ]. Severe COVID-19 was defined as COVID-19 episode that required supplemental oxygen therapy, intensive care unit (ICU) stay or treatment with steroids or remdesivir. Vaccination status categorization was based on vaccination records, when available, or patients’ self-reported status. SARS CoV-2 variants classification was based on the dominant variant at the time of SARS-CoV-2 diagnosis as captured by the Zambia’s genomic surveillance system and submitted to the Global Initiative on Sharing All Influenza Data (GISAID) rather than sequenced specimens from patients [ 48 ]. Diabetes, hypertension, or deep vein thrombosis/pulmonary embolism detected at the time of SARS-CoV-2 diagnosis were categorized as newly diagnosed medical conditions. Study size For the study sample size, we assumed prevalence of long COVID at 30% and a precision corresponding to the effect size of 5%. The prevalence or Cochrane formula (described elsewhere) was used to calculate the minimum sample size of 323 [ 49 ]. Study participants were included in the study if they were COVID-19 patients presenting in PAC-19 clinics for follow-up care after discharge from hospital or outpatient episodic care and had their information abstracted to the clinics’ REDCap electronic database. A full enumeration of all PAC-19 clinic attendees was however considered for higher accuracy and precision. For the longitudinal sub-analysis, patients were excluded from the analysis if they attended a PAC-19 clinic only once. Statistical Analysis At descriptive statistics we reported frequencies with proportions for categorical variables and medians with the interquartile range (IQR) for non-normally distributed numeric variables assessed using the Shapiro-Wilk test. The Pearson Chi-square and Kruskal Wallis tests for proportions and Wilcoxon rank sum test for medians were used to estimate the direction and magnitude of association. An unadjusted and adjusted logistic regression model was fitted to assess for factors associated with having long COVID at first visit to a PAC-19 clinic. The main cross-sectional analysis was for patients hospitalized during acute COVID-19 (inpatients) to maintain key variables in the analysis. At multivariable analysis, we adjusted for age, presence of newly diagnosed medical conditions, presence of pre-existing comorbidities, and COVID-19 episode details (i.e., hospital length of stay, and presence of severe COVID-19). Covariate inclusion criteria at multivariable analysis were based on theoretical relevance to the study and statistical significance (p-value≤0.2). We also conducted an additional cross-sectional analysis that included both inpatients and outpatients during acute infection to assess for association of hospitalization during acute COVID-19 with long COVID. For the longitudinal sub-analysis, we a fitted mixed effects model to account for the heterogeneity in long COVID i.e., the differences between patients and within patients across repeated observations or PAC-19 clinic visits. An unadjusted and adjusted mixed effects model was separately fitted for acute COVID-19 inpatients only and additionally for both inpatients and outpatients. The patient was the random effects term for the model. Since there was dependence in the data, we also reported the conditional intraclass correlation (ICC) which quantified the variance in long COVID heterogeneity that was attributable to between patients and within patients across PAC-19 visits. Only covariates with 10% missingness were included at multivariable analysis. Model selection was based on goodness-of-fit statistics (i.e., adjusted pseudo R 2 , Akaike information criteria, Bayesian information criteria and log-likelihood value). Analysis was done in R software version 4.3.2 (R Foundation for Statistical Computing) and statistical significance was considered at p<0.05. Ethical considerations This study was preconceived during the development of clinical and operational guidelines for the management of PAC-19 patients in Zambia. The study obtained ethical clearance (waiver for informed consent) from the University of Zambia Biomedical Research Ethics Committee (Ref No. 2711-2022), approval from the Zambia National Health Research Authority (Ref No: NHRA0002/26/05/2022) and was determined to be non-research according to the U.S Centers for Disease Control and Prevention (CDC) policy and applicable federal law (See e.g., 45 C.F.R. part 46.102(l)(2), 21 C.F.R. part 56; 42 U.S.C. §241(d); 5 U.S.C. 552a; 44 U.S.C.3501 et seq.). CDC investigators did not interact with patients or have access to personally identifiable information but participated in protocol development and analysis of anonymized data. Results In total, 1,359 patients that attended PAC-19 clinics from August 2020 to January 2023 were in the cross sectional analysis ( Fig 1 ). Of these patients, 548 (40.3%) patients that had ≥2 PAC-19 clinic visits were included in the longitudinal sub-analysis. Most patients (919/1,087, 84.5%) were hospitalized during acute COVID-19 ( Table 1 ). Overall, patients’ median age was 53 (IQR: 41-63) years, and 693 (52.9%) were female. Most patients (58.0%) were from Lusaka, where the first two PAC-19 clinics were initially set up. Nearly half of the patients (46.9%) were diagnosed with COVID-19 when delta was the dominant variant ( Fig. 2 ). The median time since COVID-19 diagnosis when patients presented for care in PAC-19 clinics was 4 (IQR:2-6) weeks. Download figure Open in new tab Fig 1: Analysis flow diagram of PAC-19 clinic patients in Zambia, August 2020 – January 2023 Download figure Open in new tab Fig 2: PAC-19 clinic patients’ attendance by date of diagnosis, August 2020 – January 2023 View this table: View inline View popup Table 1: Demographic and Clinical Characteristics of Patients who Presented for Care in PAC-19 Clinics in Zambia, Aug. 2020‒Jan. 2023 At baseline, 654 (48.1%) patients overall, reported having had pre-existing comorbidity. Among these patients, hypertension (n=465, 71.1%), diabetes (n=172, 26.3%), HIV (n=165, 25.2%) and cardiovascular disease (n=73, 11.2%) were commonly (frequency of ≥10%) reported (S1 Table). One hundred nineteen (8.8%) patients had been diagnosed with new medical conditions at the time of SARS-CoV-2 diagnosis. Of these patients, hypertension and diabetes were detected at SARS-CoV-2 diagnosis in 68 (53.8%) and 64 (53.8%) patients, respectively. Among the hospitalized acute COVID-19 patients, the median length of stay was 7 days (IQR:4-15 days). Of these inpatients, 686 (74.6%) were categorized as having had severe COVID-19. The medium time from the date of COVID-19 diagnosis to when patients presented for care in a PAC-19 clinic was 4 weeks (IQR: 2-6 weeks). At first visit to a PAC-19 clinic, 274 (29.8%) hospitalized patients had long COVID. Among these long COVID patients, commonly reported symptoms included cough (38.7%), fatigue (38.5%), shortness of breath (26.5%), chest pain (20.9%), headache (14.8%), muscles aches/pain (14.1%), palpitations (12.5%), joint aches/pain (11.9%), and forgetfulness or brain fog (8.0%). Among the outpatients, 103 (23.4%) had long COVID, bringing the overall number of long COVID patients to 377 (27.7%). Of all patients, 232 (28.9%) patients had worse or same (limitations in daily activities) functional status since acute COVID-19. The functional status patients commonly reported difficulty in undertaking was walking long distances greater than 1km (22.6%), day-to-day work/school (cognitive) activities (19.4%), standing for ≥30 minutes (19.4%), taking care of household tasks (17.8%), and self-care (activities like bathing and dressing) – 15.1%. Fifty-nine (6.6%) patients were referred to specialist care, including cardiology (35.6%), endocrinology (33.9%), psychiatry (25.4%), pulmonology (18.6%), physiotherapy (11.0%), and nephrology (1.7%). Overall, 243 (23.5%) patients had been vaccinated before being diagnosed with SARS-CoV-2, representing 28.5% of patients seen at PAC-19 clinics from April 2021 when COVID-19 vaccines first became available in Zambia. Of these vaccinated patients, 102 (42%%) received Johnson and Johnson’s Janssen (Ad26.COV2.S), 97 (39.9%%) received AstraZeneca (AZD1222), 41 (16.9%%) did not know the vaccine type they received, and 3 (1.2%%) received Pfizer-BioNTech (BNT162b2). Fifty-seven (23.4%) had received a full series of vaccines >14 days prior to their date of SARS-CoV-2 diagnosis, 31 (12.7%) were partially vaccinated (i.e., 2nd dose not yet received), 10 (4.1%) were diagnosed with SARS-CoV-2 within 14 days of being vaccinations while 148 (60.9%) had missing vaccination dates to be classified. Patients with pre-existing comorbidities (adjusted odds ratio [aOR]: 1.50; 95% confidence interval [CI]: 1.02-2.21), and with hospital length of stay of 8-14 and ≥15 days were associated with significantly higher odds of long COVID (aOR: 1.98; CI: 95% 1.08-3.74, and aOR: 5.37; 95% CI: 2.99-10.0, respectively) - Table 2 . Patients who had severe COVID-19 had 3.23-fold (95% CI: 1.68-6.75) higher odds of presenting with long COVID. Independently, vaccinated patients had non-significant reduced likelihood of long COVID (OR: 0.94; 95% CI: 0.64-1.36) while those who were referred to specialist services had 1.88-fold (95% CI: 1.00-3.48; p-value=0.045) increased likelihood of long COVID. View this table: View inline View popup Table 2: Factors associated with long COVID at first visit to PAC-19 clinic among patients hospitalized for acute COVID-19 in Zambia, August 2020 – January 2023 (N=919) In the additional cross-sectional analysis that included both inpatients and outpatients during acute COVID-19 (S2 Table), inpatients were associated with non-significant increased odds of long COVID (aOR: 1.05; 95% CI: 0.72-1.55). Patients with the presence of comorbidities were, however, associated with significantly higher odds of long COVID (aOR: 1.55; 95% CI: 1.16-2.08) while the presence of newly diagnosed medical conditions had a non-significant increase likelihood of long COVID. Patients aged 40-49 years were significantly associated with 1.79-fold increased likelihood of long COVID (95% CI: 1.03-3.22). Independently, patients referred to specialist services were 2.34 times (95% CI: 1.37-4.00) more likely to present with long COVID. Males compared to females and having been vaccinated against COVID-19 were associated with non-significant reduced odds of long COVID. In the longitudinal analysis (S1 Fig), the overall median time patients presented at a PAC-19 clinic was 7 (IQR: 4-12) weeks. Longitudinally ( Fig 3 ), the most frequently (≥5% at any PAC-19 clinic visit) reported long COVID symptoms were cough (16.9%), fatigue (16.4%), shortness of breath (10.6%), chest pain (8.4%), headache (8.3%), palpitations (6.6%) and muscle aches/pains (5.2%), and forgetfulness (3.0%). The prevalence of long COVID significantly declined (p<0.001) from 75.4% at the first PAC-19 clinic visit to 53.5% at the second visit, 59.8% at the third visit, 49.6% at the fourth visit, and 26.0% at the final visit (S3 Table). Overall, the proportion of vaccinated patients attending PAC-19 clinics increased from 20% at the first visit to 58% at the fifth visit; an increase that will statistically significant (p<0.001). Similarly, comparatively significantly (p=0.002) larger proportion of patients with comorbidities presented in subsequent PAC-19 clinic visits than at the first visit. The proportion of patients with newly diagnosed medical conditions longitudinally declined; this was, however, non-significant (p=0.953). Download figure Open in new tab Fig 3: Longitudinal frequency of most common long COVID symptoms by PAC-19 clinic visit, Aug. 2020 - Jan. 2023 We found similar associations with long COVID in the longitudinal analysis ( Table 3 ) as with the cross-sectional analysis ( Table 2 ). Across subsequent clinical visits, the odds of long COVID declined overall. Patients with hospital length of stay of ≥15 days and those with severe COVID-19 had significantly increased likelihood of presenting with long COVID (aOR: 4.30; 95% CI: 1.54-12.0, and aOR: 1.89; 95% CI: 1.02-3.49, respectively). Longitudinally, vaccinated patients had a non-significant reduced odds of long COVID (aOR: 0.78; 95% CI: 0.45-1.35). Similarly, sex, age, presence of comorbidities and newly diagnosed medical conditions were associated with non-significant likelihood of long COVID. For the longitudinal model, the conditional ICC was estimated to be 0.562; suggesting that 56.2% of the longitudinal variance in long COVID was attributable to between patient differences. View this table: View inline View popup Table 3: Factors longitudinally association with long COVID among acute COVID-19 hospitalized patients in Zambia, August 2020 – January 2023 (N=540) In the longitudinal sub-analysis that included both those that were inpatients and outpatients during acute COVID-19 (S4 Table), similar associations were observed as to the cross section sub-analysis (S2 Table). The likelihood of presenting with long COVID significantly (p<0.001) declined, overall, across subsequent PAC-19 clinic visits (S4 Table). The presence of comorbidities were longitudinally associated with increased odds of long COVID by a factor of 1.67 (95% CI: 1.02-2.75). Hospitalized patients during acute COVID-19, vaccinated and male patients were associated with non-significant reduced likelihood of long COVID. Similarly, order age groups and presence of newly diagnosed medical conditions were associated with non-significant, however increased, odds of long COVID. Discussion Long COVID symptoms were common among patients presenting for care in specialized post-acute COVID-19 clinics in Zambia, which could represent potential substantial morbidity from COVID-19. Factors associated with long COVID in Zambia included severe COVID-19, hospital length of stay and presence of pre-existing comorbidities. Hospitalization was not significantly associated with long COVID while patients with limitations in daily activities that may have impacted on the patients’ functional status were independently associated with long COVID. Longitudinally vaccination patients had indistinguishable likelihood of long COVID and so was sex and age. A severe form of COVID-19 is known to increase the risk of an intense immune response that could lead to widespread inflammation [ 50 ]. The inflammatory response can persist post-acute infection and could have led to the immune system being dysregulated, leading to prolonged persistent symptoms and complications of COVID-19 in the patients. This could have led to observed association of severe COVID-19 long COVID as has been reported in other studies [ 35 , 36 , 51 , 52 ]. Patients with longer hospital stays may have received intensive medical interventions and additional treatments. This could have potentially affected the immune response and the body’s ability to recover from the acute COVID-19p, which in turn may have increased the likelihood of long COVID. Furthermore, patients with pre-existing comorbidities may have been more susceptible to severe COVID-19 and may have been at higher risk of developing long COVID. This is consistent with what is reported by other studies on patients with longer hospitalization stay for acute COVID-19 or pre-existing comorbidities and their association to long COVID [ 52 – 54 ]. Patients referred to specialist services may have had residual organ damage from acute COVID-19 which may have required specialist care. This may have been closely related to the observed limitations in daily activities that may have impacted on the patients’ functional status since acute COVID-19 as have been reported in a previous study [ 9 ]. Although this association was independently significant, we could not adjust for it at multivariable analysis due to missingness that resulted in listwise deletion of more than half the study sample. Furthermore, no feedback systems were in place to inform PAC-19 clinics of the outcome of specialist care of referred patients. COVID-19 vaccines have been shown to be effective at preventing symptomatic SARS-CoV-2 infections and long COVID [ 55 , 56 ]. In this study, however, vaccinated patients failed to show significant protective association between COVID vaccination and long COVID. A possible explanation for this finding might be the heterogeneity in vaccination status during the study since Zambia only began offering COVID-19 vaccination in April 2021 (i.e., right before the delta wave and ∼8 months after patients began presenting for care in PAC-19 clinics) [ 57 ]. For example, among the patients diagnosed with SARS-CoV-2 during the wild type and beta dominant variants periods, prior to publicly available COVID-19 vaccination in Zambia, only 1 patient ever reported being vaccinated. Unlike pre-existing comorbidities, newly diagnosed medical conditions had a non-significant association with long COVID. Newly diagnosed medical conditions in COVID-19 patients may have been as a result of multiorgan effects or autoimmune conditions [ 3 ]. Fewer patients, overall, had newly diagnosed medical conditions which could explain the non-significant association. Sex and age were similarly not associated with long COVID which seem to suggest that factors associated with long COVID in Zambia were largely clinical as opposed to demographic. With regards to recovery time from long COVID, most patients with long COVID had symptom resolution by the second month of follow up. Overall, we found that commonly reported long COVID symptoms in Zambia were similar to findings in other studies [ 35 , 36 , 38 , 52 ]. However, symptoms like forgetfulness (commonly reported among long COVID patients) and change in sleep were less commonly reported in our study compared to previous reports [ 17 , 20 ]. In both the cross-sectional and longitudinal analysis, inpatients compared to outpatient care during COVID-19 episode were found to be associated with indistinguishable likelihood of long COVID. One reason for this might be that those who were outpatient and attending PAC-19 clinics were a special subset of outpatients with COVID-19 (i.e., they were seeking out or were referred for follow-up care during acute COVID-19e). Furthermore, inpatients (the majority of whom had severe COVID-19) might have been more likely to be referred to PAC-19 clinic whereas those who were outpatient were likely self-referral to PAC-19 clinic meaning only those who really needed it (i.e., those with ongoing symptoms) were in this study. The findings in this study are subject to several limitations. Firstly, only patients attending PAC-19 clinics were included in the study, so other patients with long COVID who sought care elsewhere (or didn’t seek care) were not included. This potentially represents some form of selection bias within the study since other long COVID patients could have by-passed the PAC-19 clinic and presented directly to clinicians or specialist service at outpatient departments. Furthermore, PAC-19 clinics took time to scale-up throughout Zambia and some persons might still have faced difficulty accessing them. Overall, fewer than 1% of the over 344,000 confirmed COVID-19 cases in Zambia as of January 2023 presented for care in PAC-19 clinics. Secondly, COVID-19 illness history (i.e., date of SARS-CoV-2 testing, hospitalization status, vaccination history, acute COVID-19 episode details, etc.) were self-reported by patients to clinicians which cannot rule out self-serving bias. Thirdly, the study utilized routinely collected clinical information from PAC-19 clinics which had substantial missingness for some key variables such as vaccination status and referral to specialist services. Thus, these variables were not adjusted for at multivariable analyses so as to maintain sample size. And lastly, patients were not retested for SAR-CoV-2 infection at subsequent PAC-19 review visits and so the possibility of reinfection could not be ruled out. Conclusion Given the burden of COVID-19 in Zambia, the findings of a potentially substantial morbidity due to long COVID, and that yet few patients overall with COVID-19 had attended a PAC-19 clinic, scaling up PAC-19 care services and integrating into routine clinical care could improve access by patients and further aid in understanding the true burden of long COVID in Zambia. This could be coupled with efforts to expand knowledge of long COVD among clinicians and the general population in Zambia. Scaling of vaccination, may likely, provide better outcomes not only for long COVID but also during acute SARS-CoV-2 infection. Improving data quality for routine clinical data, could possibly be achieved by utilizing the existing electronic health record in Zambia (SmartCare) for all clinical encounters. Information sharing between referral care services and PAC-19 clinics could aid in understanding the outcome of long COVID among patients requiring specialist care. Disclaimer The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the US Centers for Disease Control and Prevention (CDC) or the study funders . Data Availability Data are not currently publicly available but may be obtained by a third party. The data are de-identified participant data, available with permission from the Government of the Republic of Zambia (GRZ) – Ministry of Health (MoH), info{at}moh.gov.zm. A request to access the data can be made to the corresponding author (ykh1{at}cdc.gov), who will need to get permission from GRZ (MoH) to avail the data. Protocols and statistical analysis information is available as per above. Footnotes Included figures, tables and supplementary materials. Addressed reviewers' comments from a journal the paper is under review for publication. References 1. ↵ WHO . International Health Regulations Emergency Committee on novel coronavirus in China . 2020 [cited 2022 12 May]; Available from: https://www.who.int/news-room/events/detail/2020/01/30/default-calendar/international-health-regulations-emergency-committee-on-novel-coronavirus-in-china . 2. ↵ WHO . WHO Coronavirus (COVID-19) Dashboard . 2023 [cited 2022 16 October]; Available from: https://covid19.who.int/ . 3. ↵ Raveendran , A.V. , R. Jayadevan , and S. Sashidharan , Long COVID: An overview . Diabetes Metab Syndr , 2021 . 15 ( 3 ): p. 869 – 875 . OpenUrl PubMed 4. ↵ Klok , F.A. , et al. , The Post-COVID-19 Functional Status scale: a tool to measure functional status over time after COVID-19 . European Respiratory Journal , 2020 . 56 ( 1 ): p. 2001494 . OpenUrl Abstract / FREE Full Text 5. Peghin , M. , et al. , Post-COVID-19 symptoms 6 months after acute infection among hospitalized and non-hospitalized patients . Clin Microbiol Infect , 2021 . 27 ( 10 ): p. 1507 – 1513 . OpenUrl PubMed 6. ↵ Soriano , J.B. , et al. , A clinical case definition of post-COVID-19 condition by a Delphi consensus . Lancet Infect Dis , 2022 . 22 ( 4 ): p. e102 – e107 . OpenUrl CrossRef PubMed 7. ↵ Venturelli , S. , et al. , Surviving COVID-19 in Bergamo province: a post-acute outpatient re-evaluation . Epidemiology and Infections , 2021 . 149 : p. e32 . OpenUrl 8. ↵ Ahmed , H. , et al. , Long-term clinical outcomes in survivors of severe acute respiratory syndrome and Middle East respiratory syndrome coronavirus outbreaks after hospitalisation or ICU admission: A systematic review and meta-analysis . Journal of Rehabil itation of Medicine , 2020 . 52 ( 5 ): p. jrm00063 . OpenUrl 9. ↵ Hui , D.S. , et al. , Impact of severe acute respiratory syndrome (SARS) on pulmonary function, functional capacity and quality of life in a cohort of survivors . Thorax , 2005 . 60 ( 5 ): p. 401 – 9 . OpenUrl Abstract / FREE Full Text 10. Lam , M.H. , et al. , Mental morbidities and chronic fatigue in severe acute respiratory syndrome survivors: long-term follow-up . JAMA Internal Medicine , 2009 . 169 ( 22 ): p. 2142 – 7 . OpenUrl 11. ↵ Lee , S.H. , et al. , Depression as a Mediator of Chronic Fatigue and Post-Traumatic Stress Symptoms in Middle East Respiratory Syndrome Survivors . Psychiatry Investigation , 2019 . 16 ( 1 ): p. 59 – 64 . OpenUrl 12. ↵ Thaweethai , T. , et al. , Development of a Definition of Postacute Sequelae of SARS-CoV-2 Infection . JAMA , 2023 . 329 ( 22 ): p. 1934 – 1946 . OpenUrl CrossRef PubMed 13. ↵ Vahey , G.M. , et al. , Symptom Profiles and Progression in Hospitalized and Nonhospitalized Patients with Coronavirus Disease, Colorado, USA, 2020 . Emerg Infect Dis , 2021 . 27 ( 2 ): p. 385 – 395 . OpenUrl PubMed 14. Nalbandian , A. , et al. , Post-acute COVID-19 syndrome . Nature Medicine , 2021 . 27 ( 4 ): p. 601 – 615 . OpenUrl CrossRef PubMed 15. ↵ Chippa , V. , A. Aleem , and F. Anjum , Post Acute Coronavirus (COVID-19) Syndrome . 2021 : StatPearls Publishing, Treasure Island (FL) . 16. ↵ Danesh , V. , et al. , Symptom Clusters Seen in Adult COVID-19 Recovery Clinic Care Seekers . J Gen Intern Med , 2023 . 38 ( 2 ): p. 442 – 449 . OpenUrl 17. ↵ Davis , H.E. , et al. , Characterizing long COVID in an international cohort: 7 months of symptoms and their impact . EClinicalMedicine , 2021 . 38 : p. 101019 . OpenUrl 18. ↵ WHO . Post COVID-19 condition (Long COVID) . 2022 [cited 2023 6 July]; Available from: https://www.who.int/europe/news-room/fact-sheets/item/post-covid-19-condition . 19. ↵ Carfì , A. , R. Bernabei , and F. Landi , Persistent Symptoms in Patients After Acute COVID-19 . JAMA , 2020 . 324 ( 6 ): p. 603 – 605 . OpenUrl CrossRef PubMed 20. ↵ Huang , C. , et al. , 6-month consequences of COVID-19 in patients discharged from hospital: a cohort study . Lancet , 2021 . 397 ( 10270 ): p. 220 – 232 . OpenUrl CrossRef PubMed 21. ↵ Tenforde , M.W. , et al. , Symptom Duration and Risk Factors for Delayed Return to Usual Health Among Outpatients with COVID-19 in a Multistate Health Care Systems Network - United States, March-June 2020 . MMWR Morb Mortal Wkly Rep , 2020 . 69 ( 30 ): p. 993 – 998 . OpenUrl CrossRef PubMed 22. ↵ Ballering , A.V. , et al. , Persistence of somatic symptoms after COVID-19 in the Netherlands: an observational cohort study . Lancet , 2022 . 400 ( 10350 ): p. 452 – 461 . OpenUrl CrossRef PubMed 23. Ayoubkhani , D. , et al. , Risk of Long COVID in People Infected With Severe Acute Respiratory Syndrome Coronavirus 2 After 2 Doses of a Coronavirus Disease 2019 Vaccine: Community-Based, Matched Cohort Study . Open Forum Infect Dis , 2022 . 9 ( 9 ): p. ofac464 . OpenUrl CrossRef PubMed 24. Bull-Otterson , L. , et al. , Post–COVID Conditions Among Adult COVID-19 Survivors Aged 18–64 and ≥65 Years — United States, March 2020–November 2021 . MMWR Morb Mortal Wkly Rep , 2022 . 71 ( 21 ): p. 713 – 7 . OpenUrl CrossRef 25. Ceban , F. , et al. , Fatigue and cognitive impairment in Post-COVID-19 Syndrome: A systematic review and meta-analysis . Brain Behav Immun , 2022 . 101 : p. 93 – 135 . OpenUrl CrossRef PubMed 26. Xu , E. , Y. Xie , and Z. Al-Aly , Long-term neurologic outcomes of COVID-19 . Nat Med , 2022 . 28 ( 11 ): p. 2406 – 2415 . OpenUrl 27. ↵ Davis , H.E. , et al. , Long COVID: major findings, mechanisms and recommendations . Nature Reviews Microbiology , 2023 . 28. ↵ Nyasulu , P.S. , J.L. Tamuzi , and R.T. Erasmus , Burden, causation, and particularities of Long COVID in African populations: A rapid systematic review . IJID Regions , 2023 . 8 : p. 137 – 144 . OpenUrl 29. ↵ Antonelli , M. , et al. , Risk factors and disease profile of post-vaccination SARS-CoV-2 infection in UK users of the COVID Symptom Study app: a prospective, community-based, nested, case-control study . Lancet Infect Dis , 2022 . 22 ( 1 ): p. 43 – 55 . OpenUrl CrossRef PubMed 30. Morello , R. , et al. , Risk factors for post-COVID-19 condition (Long Covid) in children: a prospective cohort study . eClinicalMedicine , 2023 . 59 : p. 101961 . OpenUrl 31. ↵ Tsampasian , V. , et al. , Risk Factors Associated With Post−COVID-19 Condition: A Systematic Review and Meta-analysis . JAMA Internal Medicine , 2023 . 183 ( 6 ): p. 566 – 580 . OpenUrl 32. ↵ Frallonardo , L. , et al. , Incidence and burden of long COVID in Africa: a systematic review and meta-analysis . Scientific Reports , 2023 . 13 ( 1 ): p. 21482 . OpenUrl 33. ↵ Osikomaiya , B. , et al. , ‘Long COVID’: persistent COVID-19 symptoms in survivors managed in Lagos State, Nigeria . BMC Infectious Diseases , 2021 . 21 ( 1 ): p. 304 . OpenUrl CrossRef PubMed 34. ↵ Müller , S.A. , et al. , Prevalence and risk factors for long COVID and post-COVID-19 condition in Africa: a systematic review . Lancet Glob Health , 2023 . 11 ( 11 ): p. e1713 – e1724 . OpenUrl 35. ↵ Osikomaiya , B. , et al. , ’Long COVID’: persistent COVID-19 symptoms in survivors managed in Lagos State, Nigeria . BMC Infect Dis , 2021 . 21 ( 1 ): p. 304 . OpenUrl CrossRef PubMed 36. ↵ Dryden , M. , et al. , Post-COVID-19 condition 3 months after hospitalisation with SARS-CoV-2 in South Africa: a prospective cohort study . Lancet Glob Health , 2022 . 10 ( 9 ): p. e1247 – e1256 . OpenUrl 37. ↵ Moyo , E. , et al. , Risk factors and clinical presentations of long COVID in Africa: A scoping review . Journal of Infection and Public Health , 2023 . 16 ( 12 ): p. 1982 – 1988 . OpenUrl 38. ↵ Zulu , J.E. , et al. , Two-month follow-up of persons with SARS-CoV-2 infection-Zambia, September 2020: a cohort study . Pan Afr Med J , 2022 . 41 : p. 26 . OpenUrl 39. ↵ Mulenga , L.B. , et al. , Prevalence of SARS-CoV-2 in six districts in Zambia in July, 2020: a cross-sectional cluster sample survey . Lancet Glob Health , 2021 . 9 ( 6 ): p. e773 – e781 . OpenUrl 40. Sheppard , R.J. , et al. , Using mortuary and burial data to place COVID-19 in Lusaka, Zambia within a global context . Nat Commun , 2023 . 14 ( 1 ): p. 3840 . OpenUrl 41. ↵ Gill , C.J. , et al. , What is the prevalence of COVID-19 detection by PCR among deceased individuals in Lusaka, Zambia? A postmortem surveillance study . BMJ Open , 2022 . 12 ( 12 ): p. e066763 . OpenUrl Abstract / FREE Full Text 42. Heilmann , E. , et al. , SARS-COV-2 seroprevalence trend among pregnant women in Zambia, 2021-2022, in Conference on Retroviruses and Opportunistic Infections (CROI) . 2023 : Seattle, Washington . 43. Mumba , T.K. , et al. , Seroprevalence survey of SARS-CoV-2, community behaviors, and practices in Kansanshi and Kalumbila mining towns . Frontiers in Public Health , 2023 . 11 . 44. Shanaube , K. , et al. , SARS-CoV-2 seroprevalence and associated risk factors in periurban Zambia: a population-based study . Int J Infect Dis , 2022 . 118 : p. 256 – 263 . OpenUrl 45. ↵ Lewis , H.C. , et al. , SARS-CoV-2 infection in Africa: a systematic review and meta-analysis of standardised seroprevalence studies, from January 2020 to December 2021 . BMJ Glob Health , 2022 . 7 ( 8 ). 46. ↵ Ministry of Health (Zambia) . Clinical Guidance for Management of Patients with Coronavirus Disease 2019 (COVID-19) . 2020 [cited 2023 12 August]; Available from: https://www.moh.gov.zm/?wpfb_dl=181 . 47. ↵ Ministry of Health, Clinical and Operational Guidelines for the Management of Post-Acute Covid-19 (PAC-19) Patients in Zambia, in Post-Acute COVID-19 Clinical and Operational Guidelines . 2022 , Ministry of Health (Zambia) : Lusaka . 48. ↵ GISAID . EpiCov . 2023 [cited 2023 12 August]; Available from: https://www.epicov.org/epi3/frontend#24d000 . 49. ↵ Charan , J. and T. Biswas , How to calculate sample size for different study designs in medical research? Indian J Psychol Med , 2013 . 35 ( 2 ): p. 121 – 6 . OpenUrl CrossRef PubMed 50. ↵ Wong , R.S.Y ., Inflammation in COVID-19: from pathogenesis to treatment . Int J Clin Exp Pathol , 2021 . 14 ( 7 ): p. 831 – 844 . OpenUrl 51. ↵ Zhang , H.P. , et al. , Recent developments in the immunopathology of COVID-19 . Allergy , 2023 . 78 ( 2 ): p. 369 – 388 . OpenUrl 52. ↵ Fernández-de-las-Peñas , C. , et al. , Prevalence of post-COVID-19 symptoms in hospitalized and non-hospitalized COVID-19 survivors: A systematic review and meta-analysis . European Journal of Internal Medicine , 2021 . 92 : p. 55 – 70 . OpenUrl 53. Cirulli , E.T. , et al. , Long-term COVID-19 symptoms in a large unselected population . medRxiv , 2020 : p. 2020.10.07.20208702. 54. ↵ Asadi-Pooya , A.A. , et al. , Risk Factors Associated with Long COVID Syndrome: A Retrospective Study . Iran J Med Sci , 2021 . 46 ( 6 ): p. 428 – 436 . OpenUrl 55. ↵ Rane , M.S. , et al. , Effectiveness of Covid-19 vaccines against symptomatic and asymptomatic SARS-CoV-2 infections in an urgent care setting . Vaccine , 2023 . 41 ( 4 ): p. 989 – 998 . OpenUrl 56. ↵ Britton , A. , et al. , Association of COVID-19 Vaccination With Symptomatic SARS-CoV-2 Infection by Time Since Vaccination and Delta Variant Predominance . Jama , 2022 . 327 ( 11 ): p. 1032 – 1041 . OpenUrl CrossRef PubMed 57. ↵ Chanda , D. , et al. , COVID-19 Vaccine Effectiveness Against Progression to In-Hospital Mortality in Zambia, 2021-2022 . Open Forum Infect Dis , 2022 . 9 ( 9 ): p. ofac469 . OpenUrl CrossRef View the discussion thread. Back to top Previous Next Posted March 11, 2024. Download PDF Supplementary Material Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Clinical Characteristics and Factors Associated with Long COVID in Zambia, August 2020 to January 2023: A Mixed Methods Design Message Subject (Your Name) has forwarded a page to you from medRxiv Message Body (Your Name) thought you would like to see this page from the medRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Clinical Characteristics and Factors Associated with Long COVID in Zambia, August 2020 to January 2023: A Mixed Methods Design Warren Malambo , Duncan Chanda , Lily Besa , Daniella Engamba , Linos Mwiinga , Mundia Mwitumwa , Peter Matibula , Neil Naik , Suilanji Sivile , Simon Agolory , Andrew Auld , Lloyd Mulenga , Jonas Z. Hines , Sombo Fwoloshi medRxiv 2024.01.17.24301423; doi: https://doi.org/10.1101/2024.01.17.24301423 Share This Article: Copy Citation Tools Clinical Characteristics and Factors Associated with Long COVID in Zambia, August 2020 to January 2023: A Mixed Methods Design Warren Malambo , Duncan Chanda , Lily Besa , Daniella Engamba , Linos Mwiinga , Mundia Mwitumwa , Peter Matibula , Neil Naik , Suilanji Sivile , Simon Agolory , Andrew Auld , Lloyd Mulenga , Jonas Z. Hines , Sombo Fwoloshi medRxiv 2024.01.17.24301423; doi: https://doi.org/10.1101/2024.01.17.24301423 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Epidemiology Subject Areas All Articles Addiction Medicine (573) Allergy and Immunology (865) Anesthesia (303) Cardiovascular Medicine (4457) Dentistry and Oral Medicine (445) Dermatology (383) Emergency Medicine (610) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1517) Epidemiology (15244) Forensic Medicine (30) Gastroenterology (1132) Genetic and Genomic Medicine (6620) Geriatric Medicine (669) Health Economics (1002) Health Informatics (4557) Health Policy (1372) Health Systems and Quality Improvement (1615) Hematology (543) HIV/AIDS (1272) Infectious Diseases (except HIV/AIDS) (15936) Intensive Care and Critical Care Medicine (1106) Medical Education (624) Medical Ethics (147) Nephrology (670) Neurology (6634) Nursing (346) Nutrition (999) Obstetrics and Gynecology (1148) Occupational and Environmental Health (957) Oncology (3348) Ophthalmology (980) Orthopedics (369) Otolaryngology (421) Pain Medicine (436) Palliative Medicine (130) Pathology (665) Pediatrics (1696) Pharmacology and Therapeutics (693) Primary Care Research (714) Psychiatry and Clinical Psychology (5463) Public and Global Health (9256) Radiology and Imaging (2210) Rehabilitation Medicine and Physical Therapy (1371) Respiratory Medicine (1198) Rheumatology (598) Sexual and Reproductive Health (716) Sports Medicine (532) Surgery (714) Toxicology (99) Transplantation (289) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'a0313a02ea8b4193',t:'MTc4MDAxMjkwNw=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();