Burden of febrile illness complications and determinants of typhoid fever complications in the Ashanti region of Ghana
1School of Public Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
2Department of Statistics and Actuarial Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
3Department of Molecular Medicine, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
4Department of Clinical Microbiology, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
5Department of Medical Diagnostics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
6International Vaccine Institute, SNU Research Park, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826 Korea, Republic of Korea
*Portia Boakye Okyere E-mail: portiaboky@gmail.com (PBO)Abstract
Background and Aim
Typhoid fever remains a significant global public health concern and ranked among the top ten causes of outpatient illnesses in Ghana from 2020 to 2022. Identifying the risk factors associated with its complications is crucial for reducing mortality. This study aimed to assess the prevalence, types, and risk factors of complications in febrile patients, with a specific focus on typhoid fever in the Ashanti region of Ghana.
Method
Clinical data from 238 patients with positive blood cultures, obtained from the surveillance for Severe Typhoid in Africa program between May 2016 and September 2019 were analysed. Statistical reduction techniques were used to identify key variables, and logistic regression identified factors independently associated with typhoid complications.
Results
The overall prevalence of complications amongst the febrile patients was 55% (131/238). S. Typhi and non-S. Typhi infections resulted in 38.9% (28/72) and 62% (103/166) complications, respectively. In general, notable complications associated with febrile illnesses included sepsis (23.5%, 56/238), severe anaemia (19.3%, 46/238), gastrointestinal bleeding (3.8%, 9/238), and intestinal perforation (2.5%, 6/238). Typhoid fever contributed to 18.1% (13/72) of sepsis, 8.3% (6/72) of gastrointestinal bleeding, and 5.6% (4/72) each for severe anaemia and intestinal perforation. Mortality rates were 1.4% (1/72) in S. Typhi patients and 2.4% (4/166) in non-S. Typhi patients. Complications were independently associated with a longer duration of illness before hospital visit (AOR 8.6, 95%CI 1.2-64.7, p=0.035) and rural residence (AOR 0.1, 95%CI 0, 0.7, p=0.024).
Conclusion
The study highlights a significant burden of complications among febrile patients in Ghana, with typhoid fever as a major concern. Delayed healthcare-seeking behaviour significantly increased the risk of typhoid complications, while the rural residence appeared to be protective. These findings underscore the need for timely diagnosis, prompt treatment, and health education, especially in urban areas. Strengthening preventive strategies, including vaccination, remains essential to reducing typhoid-related complications and mortality.
Article notes
Competing Interest Statement
The authors have declared no competing interest.
Funding Statement
Yes
Introduction
Fever is among the most common symptoms reported by patients seeking healthcare, especially in poor-resource countries, and may occur either in isolation or alongside other symptoms [1]. Several febrile illnesses, including typhoid fever (hereafter referred to interchangeably as typhoid), are life-threatening conditions [2,3]. Typhoid, caused by Salmonella enterica serotype Typhi (S. Typhi), is a systemic febrile disease specific to humans. It is transmitted through the ingestion of water or food contaminated by the faeces of transient or chronic carriers. Annually, typhoid causes an estimated 11.9 to 26.9 million cases and 128 to 216.5 thousand deaths globally [4,5]. The disease remains a major public health concern, particularly in low- and middle-income countries, including Asia and Africa, where 18 million cases are reported each year [6].
In Ghana, typhoid ranked among the top 10 outpatient illnesses from 2020 to 2022, with 389 cases per 100,000 person-years of observation among children under 15 years [7,8]. Clinically, Typhoid presents with diverse signs and symptoms that mimic other febrile and gastrointestinal disorders, making accurate diagnosis challenging and increasing the risk of complications. Typhoid complications, including typhoid intestinal perforation (TIP), gastrointestinal bleeding, and encephalopathy, affect up to 15% of patients, particularly those with prolonged illness lasting over two weeks, with higher prevalence reported in Africa [9,10].
Several factors contribute to the increased risk of typhoid complications, including extreme age, male sex, antimicrobial resistance, prior antibiotic use, and delays in seeking medical care. Delayed medical intervention can lead to late diagnosis and treatment, further exacerbating the risk of complications. Effective management of typhoid hinges on understanding these risk factors, accurate diagnosis, timely antimicrobial therapy, and prevention through vaccination [11]. Prompt diagnosis and treatment are crucial to averting complications and reducing mortality [12].
While global data on typhoid complications are available, including from Africa [13,14], evidence from Ghana remains scarce regarding prevalence, types, and associated risk factors. To the best of our knowledge, typhoid intestinal perforation is the most frequently documented complication, while others may be underreported [15–21]. This study addresses a critical knowledge gap providing novel data on typhoid complications in Ghana and offering evidence to inform public health interventions and clinical management strategies. Specifically, we aimed to assess the prevalence, types, and risk factors of complications among febrile patients, with a focus on typhoid fever in the Ashanti region of Ghana. We hypothesised that delayed treatment due to prolonged symptoms before seeking healthcare increases the risk of complications.
Methods
Study settings
The study involved a retrospective analysis of surveillance data under the Severe Typhoid in Africa (SETA) program established in Ghana between May 2016 and September 2019. The design and methodology of the SETA study are published elsewhere [22]. Briefly, the SETA program conducted healthcare facility-based surveillance across Burkina Faso, the Democratic Republic of Congo, Ethiopia, Madagascar, Nigeria, and Ghana actively screening for invasive salmonellosis and typhoid fever complications using a standardised protocol. In Ghana, SETA exclusively recruited patients residing in the Ashanti region from two healthcare facilities: Komfo Anokye Teaching Hospital (KATH) in Kumasi and Agogo Presbyterian Hospital (APH) in Asante Akyem Agogo (Fig 1). APH is the primary referral hospital located in the Agogo township in the Asante Akim North district with a population of 85,788. The APH with a bed capacity of 350 and 125, 918 outpatient department attendances per year, provides healthcare services for patients all over Ghana and beyond [23,24]. KATH, a tertiary medical centre and teaching hospital situated in the Kumasi metropolis with a population of 443,981 [23,25], serves as the regional hospital for the Ashanti region and also sees patients from 11 other regions in Ghana. With a bed capacity of 1,200, it registers 40,000 in-patients and attends to 380,000 out-patient cases annually (KATH, 2019). The study obtained clinical and laboratory data from consenting eligible patients in the in-patient and out-patient units of KATH and APH hospitals. Blood cultures were used to confirm typhoid infection. Eligibility criteria included patients presenting with current fever (body temperature ≥38°C tympanic/rectal or ≥37.5°C axillary) or a history of fever lasting ≥3 consecutive days within the 7 days preceding enrollment.
Ethical approval
The SETA Ghana study protocol received ethical approval from the Committee on Human Research, Publication and Ethics (CHRPE) of the Kwame Nkrumah University of Science and Technology, School of Medical Sciences/Komfo Anokye Teaching Hospital. The initial approval was granted in April 2016 (CHPRE/AP/219/16) with renewals obtained throughout the data collection period (May 2016 to September 2019). Before enrollment, voluntary written informed consent was obtained from all participants, in the case of minors, from parents or legal guardians. For this study data were accessed in 20th February 2023. The dataset was fully de-identified prior to access and the authors did not have access to any personally identifying information.
Study variables
Using a standardised data abstraction form (S1 Appendix), data related to patients with positive blood culture growth were extracted from the SETA-Ghana database. The abstracted data contained a mix of continuous and categorical variables, covering demographic, clinical, and laboratory aspects for both inpatients and outpatients. The variables measured in days included: the duration of hospitalisation, duration of current fever, duration of past fever, duration of other symptoms before hospital visit (from the date fever started to the date of first healthcare assessment), and duration of illness before diagnosis (from the date symptoms started to the date blood culture ended). Based on clinical relevance to typhoid complication risk factors and a review of the literature, the following continuous data were categorised: an elevated white cell count (defined as >15×103/uL), a low white cell count (defined as <4×103/L), a low platelet count (defined as <140×103/uL), low haemoglobin (Hb) (Hb <10g/dL in children ≤5 years or Hb <11.0g/dL in older children and adults).
In this study, we defined complications as the occurrence of one or more severe systemic conditions, including gastrointestinal bleeding (visible blood/melena or positive blood stool test), intestinal perforation (suspected or confirmed at surgery), encephalopathy (delirium, obtundation, stupor, or coma), meningitis (suggestive symptoms, CSF culture examination), myocarditis (abnormal cardiac rhythm and ventricular failure with an associated abnormality on the ECG or ultrasound evidence of a pericardial effusion),hepatitis (visible jaundice, hepatomegaly, elevated serum glutamic-oxaloacetic transaminase (SGOT >400 IU/L) and/or elevated serum glutamic-pyruvic transaminase (SGPT >400 IU/L)), cholecystitis (right upper quadrant pain and tenderness without evidence of hepatitis, enlarged/thickened wall gall bladder), pneumonia (respiratory symptoms, abnormal chest X-ray infiltrates), severe anemia (hematocrit <20%), focal infection (abscess drainage culture), renal impairment (creatinine ≥175μmol/L), a clinical and/ laboratory diagnosis of sepsis, gastritis, other liver diseases, appendicitis, central nervous system infection (CNS), requiring blood transfusion, or resulting in death.
Microbiological methods
Under sterile conditions, 5-8 mL of blood from children and 10-14 mL from adults were drawn into BACTEC bottles (Becton-Dickenson, USA) at enrollment. The BACTEC bottles were incubated for up to 5 days in BACTEC 9050 automated incubator. Vials which flagged positive cultures underwent Gram staining and were plated on blood, chocolate or MacConkey agar. Gram-negative isolates were identified using API-20E and API-NH (Biomérieux, France), while Gram-positive Staphylococcus aureus was confirmed via coagulase testing. Antimicrobial susceptibility testing followed a modified Bauer-Kirby disc diffusion method, with inhibition zones interpreted according to the 2015 Clinical and Laboratory Standards Institute (CLSI) guidelines [26]. The antimicrobials tested, included: ampicillin (10µg), chloramphenicol (30µg), cotrimoxazole (1.25/23.75µg), ciprofloxacin (5µg), cefoxitin (30µg), ceftazidime (30µg), ceftriaxone/cefotaxime (30µg), cefuroxime (30µg), nalidixic acid (30µg) and tetracycline (30µg). Isolates were stored in microbank beads (Pro-labs Diagnostics Inc, UK) at −80°C and later sub-cultured on nutrient agar. Minimum inhibitory concentrations MICs for ciprofloxacin (0.008μg/mL to 4μg/mL) and nalidixic acid (0.5μg/mL to 512μg/mL) were determined using E-test strips (Biomérieux, France) per 2015 CLSI guidelines. Escherichia coli ATCC® 25922 and Staphylococcus aureus ATCC® 25923 served as control strains. An isolate was classified as multi-drug resistant (MDR) if it was resistant to all three antibiotics: ampicillin, chloramphenicol and cotrimoxazole, also known as first-line antibiotics against S. Typhi infection. In addition, it was defined as other multiply resistant if it showed resistance to at least two antibiotics. Resistance was determined using CLSI breakpoints, with intermediate and resistant categories classified as resistant.
Selection criteria for study participants
Between 2016 and 2019, 2,196 febrile patients were recruited, and blood samples collected from 2174. Among these, 244 had positive blood culture growths. In total, 238 participants were included in the statistical analysis, with 6 excluded due to missing enrollment information. Seventy-two typhoid patients were identified. Of the participants whose cultures showed bacterial growth (244), 131 experienced at least one complicated health condition, with 28 cases resulting from those with typhoid fever, Fig 2.
Statistical Analysis
All variables considered in this study were subjected to statistical data reduction techniques to avoid over-parameterisation, which can undermine inference quality due to too many explanatory variables [27]. We employed factor analysis with Promax rotation for continuous data reduction. For categorical data, we applied a chi-square test of independence, with a statistical significance of p≤0.05, using the patient’s complication status as the dependent variable. The reduced data were then analysed and presented in tables and figures stratified by causative agents (non-S. Typhi and S. Typhi) and across specific age groups (≤ 1 year, 2-5 years, 6–15 years, and ≥ 16 years). Continuous data were summarised with the median and interquartile range and compared using the Mann-Whitney U-test. Proportions were assessed using the Chi-squared test or Fisher’s exact test as appropriate. For logistic regression analysis, continuous variables including fever days, other symptoms days and days ill before diagnosis were categorised based on whether they fell below the median of their respective combined distributions. Univariate logistic regression identified risk factors and reported them as odds ratios (OR) with 95% confidence intervals (95% CI). Variables significant at p<0.10 in the typhoid univariate analyses were included in a multivariate model. Independent factors associated with typhoid complications were determined using a backward stepwise approach, with variables in the final model significant at p<0.05. All analyses were conducted using STATA version 14 (StataCorp, Texas, USA).
Identification of key risk factors
A total of 58 variables, comprising 20 continuous and 38 categorical data, were included in the data reduction analysis using factor analysis and the chi-square test of independence.
Component factor analysis for continuous variables
Summary statistics of the variables used in the factor analysis indicated that none followed a normal distribution (p< 0.05) (Table 1 in S2 Appendix). A preliminary inspection of the Spearman correlation matrix identified 21 significant correlations among the variables (Table 2 in S2 Appendix). Although all correlation coefficients remain <1, collinearity was detected between the variables “current fever” and “history of fever,” with a Rho=1.000. Consequently, “current fever” was excluded from further analysis. Subsequent Kaiser-Meyer-Olkin (KMO) tests were conducted to evaluate the data suitability for factor analysis [28,29]. The results initially fell short of the acceptable range with KMO1=0.44, which is below the adequacy criterion of 0.5, both overall and individually. The dataset eventually achieves an acceptable overall KMO value of 0.61 at KMO2. However, the variable “creatinine” fails to meet the adequacy criterion with KMO = 0.38. Finally, an overall KMO value of 0.65 was achieved at KMO3, indicating the data appropriateness for factor analysis with 14 factors despite initial shortcomings (Table 3 in S2 Appendix). Moreover, Bartlett’s test showed that the correlations, when taken collectively, are significant at the p<0.001. Table 4 in S2 Appendix lists the eigenvalues for the 14 possible factors, and based on the Kaiser rule of retaining factors with eigenvalues >1.0, four factors were retained. These four factors explain 98% of the total variance of the 14 factors, demonstrating that they sufficiently capture the underlying data structure. Therefore, these four factors were retained for further analysis. We then examined the factor pattern in Table 5 in S2 Appendix for significant factor loadings. The Promax rotation technique was applied to improve interpretation since the unrotated factor matrix did not show a clear factor loading pattern. In the rotated factor solution, each variable had a significant loading (>0.60) on only one factor, except for Respiratory rate (RESRT), Platelets (PLT), and SGPT, which had no significant loadings on any of the four factors considered. Consequently, these variables with insignificant loadings (RESRT, PLT, and SGPT) were removed from the analysis, leaving 11 variables for further consideration. The factor analysis was then re-conducted with the remaining 11 variables. Applying the Kaiser rule and inspecting the scree plot led to the retention of three factors (Fig. 1 in S2 Appendix), which accounted for 93% of the variance. This high level of explained variance indicates that these three factors provide a robust and simplified model for identifying risk factors for typhoid complications in Ghana, and are sufficient for capturing the essential information from the original variables.
Next, we named each factor based on the variables with significant loadings from Table 6 in S2 Appendix (Promax rotated factor pattern). Factor 1, which loads highly onto AGE, systolic BP (BPSYS), diastolic (BPDIA), and weight (WGHT) was named “Risk of hypertension.” Factor 2, with significant loadings on white blood cells (WBC), hemoglobin (Hb), and hematocrit (HCT), was termed “hematological profile.” Finally, Factor 3, based on significant loadings from duration of other symptoms (SYMPD), duration of fever before the hospital visit (FEVERD), and duration of illness before proper diagnosis (TRTD), was named “Treatment delay.” We used these 10 variables as surrogates in further analysis, however, they retained their original names in case any were found to be significantly associated with typhoid fever complications.
Chi-square test of independence for categorical data
Excluding antimicrobials, we applied Pearson’s chi-square test to 38 categorical variables to identify key variables associated with the occurrence of complications (grouped as Yes/No) (as detailed in Table 7 in S2 Appendix). Variables with a p≤0.10 were considered statistically significant. These included “hospital site,” “comorbidities,” “pathogenicity (S. Typhi),” “drug exposures before hospital visit (antibiotics and other drugs),” and “signs and symptoms (such as abdominal pain, shortness of breath, diarrhoea, visible blood in stool and prostration or exhaustion)”.
Results
Pathogen Distribution
This study identified various pathogens and contaminants among participants with complications, showing a significant association with all ages (p=0.001). Pathogens included S. Typhi (21.4%, 28/131), Salmonellae Typhimurium (0.8%, 1/131), other non-typhoidal Salmonellae (9.2%, 12/131), Staphylococcus aureus (4.6%, 6/131), E. coli (3.8%, 5/131), Klebsiella spp. (3.1%, 4/131) and Streptococcus pneumoniae (2.3%, 3/131). Contaminants were Coagulase-Negative Staphylococci (CNS) (33.6%, 44/131), Micrococcus spp. (3.8%, 5/131), Bacillus sp. (3.1%, 4/131), and Viridans streptococci (3.1%, 4/131), etc. (Fig 3).
Description of the reduced variables
Further analyses of the reduced dataset encompassed 28 variables (10 continuous and 18 categorical) involving 238 participants, predominantly 84% (200/238) children (<16 years) and 16% (38/238) adults (≥16 years). Table 1 outlines the distribution of study characteristics stratified by age groups. Hospital site distribution showed notable disparities, with a higher representation of 6-15-year-olds (39.4%, 52/132) in the rural (APH) and 0-1-year-olds (41.51%, 44/106) in urban (KATH) settings. Children aged 6-15 years exhibited prolonged febrile illness durations before seeking medical attention, with median delays of 5 days for fever symptoms, 6 days for other symptoms, and 9 days before diagnosis. BPSYS irregularities were significantly more prevalent in children compared to adults (p=0.027), notably affecting 84% (21/25) of those aged 6-15 years. The median weight varied significantly across age groups: 8.3 kg for 0-1 years, 24.8kg for 6-15 years, and 71kg for older patients. Comorbidities were also evidently higher among children, with 33.3% (20/60) prevalence in the 0-1 age group. Antibiotic use before hospital visits was more significant in children (<16 years) than in older patients (p=0.001). Among 6-15-year-olds, abdominal pain was prevalent in about 40% (34/86), while shortness of breath was even more common, affecting almost 91% (78/86). Hepatomegaly and splenomegaly occurred exclusively in children <16 years, with prevalences of 26.7% (23/86) in those aged 6-15 years and 16.7% (9/54) in those aged 2-6 years, respectively. Pathogen isolate distribution showed a significant predominance of S. Typhi among children <16 years, particularly in the 6-15-year age group (55.8%, 48/86).
Antibiotic susceptibility profile of isolates
Table 2 outlines the antimicrobial susceptibility profile of organisms isolated across different age groups. Approximately, 28% (40/145) of all isolates were fully susceptible to the tested antimicrobials. In children aged 6-15, 62.5% (15/24) of the isolates exhibited significant resistance to ampicillin (p=0.026), whereas resistance to chloramphenicol or cotrimoxazole was not statistically significant in any age group. Moreover, the prevalence of multidrug resistance (MDR) was highest in the 6-15 age group (26.4%, 14/53), followed by the >16 years age group (47.6%, 10/21). Among isolates from children aged 0-1 year, 27.3% (6/22) were significantly resistant to ceftazidime (p=0.043), while 40.9% (9/22) showed resistance to ceftriaxone/cefotaxime (p=0.038). In contrast, more than 69% (18/26) of isolates from patients older than 16 years demonstrated a strong association with tetracycline resistance (p<0.001). Of the 145 isolates, 77 (53.1%) were resistant to two or more antibiotics, with the highest burden observed in children aged 6-15 years 27/61(44.3).
Prevalence of complications
Table 3 summarises disease complications across age groups of bacterial isolates. Overall, 55% (131/238) of patients experienced complications, with 49.6% (118/238) occurring in children aged ≤15 years and 5.5% (13/238) in those >15 years. S. Typhi and non-S. Typhi caused 38.9% (28/72) and 62.1% (103/166) of these complications, respectively. Notably, sepsis, not previously listed as a typhoid complication by Parry, et al. [14], was observed in 18.1% (13/72) of typhoid cases, affecting 17.2% (11/64) of children ≤15 years and 25% (2/8) of those >15 years. In non-S. Typhi cases, sepsis occurred in 29% (39/136) of children ≤15 years and 13% (4/30) in those >15 years. Other complications in S. Typhi cases included gastrointestinal bleeding (8.3%, 6/72), intestinal perforation (5.6%, 4/72), hepatitis (1.4%, 1/72), and pneumonia (4.2%, 3/72). Non-S. Typhi patients had these complications at 1.8% (3/166), 1.2% (2/166), 1.2% (2/166), and 9.6% (16/166). The majority of S. Typhi-related gastrointestinal bleeding (9.4%, 6/64) and intestinal perforation (6.2%, 4/64) occurred in children ≤15 years. Cholecystitis, meningitis, myocarditis, and encephalopathy were exclusively observed in non-S. Typhi cases with prevalence of 1% (2/166), 1.8% (3/166), 0.6% (1/166), and 3% (5/166), respectively. Severe anaemia was more common in non-S. Typhi cases (25%, 42/166) compared to S. Typhi cases (5.6%, 4/72). Similarly, renal impairment was more prevalent in non-S. Typhi 5.4% (9/166) than in S. Typhi 1.4% (1/72). (Blood transfusions were required in 2.8% (2/72) of S. Typhi cases and 13.9% (23/166) of non-S. Typhi cases, predominantly in children ≤15 years. The overall mortality rate across all age groups was 2.1% (5/238), with 1.4% (1/72) of these deaths occurring in a child with an S. Typhi infection. However, the cause of death specifically related to typhoid was not determined in this study.
Comparison of complications in S. Typhi and non-S. Typhi febrile patients
Distinct characteristics of S. Typhi versus (vs) non-S. Typhi in febrile patients with complications are detailed in Table 4. S. Typhi complications were more common in rural areas (60.7%, 17/28), while non-S. Typhi complications were more frequent in urban areas (65.1%, 67/103). Both were notably represented in the 6-15-year age group (61% for S. Typhi, 34% for non-S. Typhi). S. Typhi patients experienced longer delays before treatment, with a median illness duration of 10.5 days before diagnosis. They also had a longer duration of fever (7 vs. 3 days) and other symptoms (7 vs. 4 days) before hospital visits compared to patients with non-S. Typhi complications. Non-S. Typhi isolates from patients with complications detected resistance to ampicillin (67.6%, 25/37), chloramphenicol (60%, 24/40), and cotrimoxazole (42.1%, 16/38), while S. Typhi isolates exhibited resistance to ampicillin (37%, 10/27), chloramphenicol (39.3%, 11/28), and cotrimoxazole (46.2%, 12/26). Cefoxitin (50%, 2/4) and ceftriaxone (35.3%, 12/34) resistance occurred exclusively in non-S. Typhi isolates, with one S. Typhi isolate resistant to cefuroxime. Ciprofloxacin and nalidixic acid resistance were higher in non-S. Typhi (32.4% and 23.1%) than in S. Typhi (15.4% and 8.3%). Tetracycline resistance was detected in 42% (13/31) of non-S. Typhi and 24% (6/25) of S. Typhi isolates. While MDR was not statistically significant (p = 0.493), other multiple resistance was significantly higher (p = 0.045) in non-S. Typhi (70.7%, 29/41) than in S. Typhi (46.4%, 13/28). S. Typhi isolates showed greater overall susceptibility (39.3%, 11/28) compared to non-S. Typhi (7.3%, 3/41) isolates.
Risk factors associated with typhoid fever complications
Table 5 shows the logistic regression analyses and the distribution of typhoid cases with and without complications. Of the 72 typhoid fever patients, 28 had complications, and 44 did not. Complications were significantly more frequent in patients from rural areas (60.7%, 17/28) than from urban areas (39.3%, 11/28). However, patients from rural areas were less likely to develop complications than urban patients (OR 0.04, 95% CI 0-0.3, p=0.002). Patients with fever for ≥6 days had 2.5 times higher odds of developing complications compared to those with shorter fever durations (<6 days) (OR 2.5, 95% CI 1.0-7.1, p=0.086). Similarly, delays in seeking treatment for other symptoms were associated with the risk of typhoid complications, with patients experiencing longer durations (≥6 days) having 3.4 times higher odds of complications (OR 3.4, 95% CI 1.1-9.9, p=0.027). Furthermore, patients with complications were more likely to have taken antibiotics before hospital visits (OR 4.7, 95% CI 1.3-17.4, p=0.019), have hepatomegaly (OR 4.0, 95% CI 1.1-14.9, p=0.039), and present with diarrhoea (OR 3.4, 95% CI 1.1-10.4, p=0.030) and abdominal pain (OR 3.0, 95% CI 1.1-8.2, p=0.033). Low haemoglobin levels were also significantly associated with complications (OR 4.9, 95% CI 1.6-14.7, p=0.005). Antibiotic resistance factors, including ampicillin (OR 3.0, 95% CI 1.0-9.3, p=0.054), chloramphenicol (OR 2.8, 95% CI 0.9-8.0, p=0.067), nalidixic acid (OR 3.6, 95% CI 0.3-42.4, p=0.303) and multidrug resistance (OR 2.0, 95% CI 0.6-6.5, p=0.234) increased the odds of typhoid complications. However, these factors were not statistically significant at the 95% CI, except for cotrimoxazole (OR 3.3, 95% CI 1.1–9.9, p = 0.039) and other multiple resistance (resistant to ≥2 antibiotics) (OR 3.7, 95% CI 1.3–11.0, p = 0.014). Additionally, patients with low Hb were about 5 times more likely to develop complications than those with normal Hb (OR 4.9 95% CI 1.6-14.7). After adjusting for potential factors in the multivariate model, typhoid complications were independently associated with longer delays in treatment (symptoms duration before hospital visit) (AOR 8.6, 95% CI 1.2-64.7, p=0.032) and the location of healthcare seeking (AOR 0.1, 95% CI 0-0.7, p=0.024). Although not statistically significant, the following factors indicated an increased odds of typhoid fever complications: diarrhoea (OR 2.7 95% CI 0.6-12.8, p=0.214), low Hb (OR 2.6 95% CI 0.5-14.1, p=0.257) and isolate resistant to two or more antibiotics (multiple resistant) (OR 3.5 95% CI 0.6-19.4, p=0.149)
Discussion
Burden of Febrile illness complications
In this study, we examined 238 febrile patients with positive blood cultures from rural and urban hospitals in the Ashanti region of Ghana. We observed a general disease complication rate of 55% (131/238), which is significantly higher than the 28% to 30% range reported in previous studies [30–32]. This higher prevalence observed in our study could likely be attributed to differences in research methodologies, study populations, and environmental contexts. Our study employed a more stringent approach to identifying and classifying pathogenic bacteria, with a particular emphasis on enhancing the detection of invasive Salmonella infections. In contrast, previous studies focused on a broader range of febrile illnesses or specific organ-related complications. Furthermore, our research encompassed patients of all age groups from resource-limited settings in both rural and urban areas, whereas earlier studies primarily concentrated on urban populations and were often limited to children or adults [30,31].These variations in methodology, population, and environmental factors likely account for the observed differences in the febrile complication rates.
Study limitation and strength
The findings of this study should be interpreted in light of certain limitations. First, the data were drawn exclusively from patients who were hospitalised or received care at two referral hospitals in the Ashanti region. This could potentially introduce selection bias, as individuals who did not access these facilities, due to financial barriers, geographic inaccessibility or preference for traditional medicine, were not captured. Consequently, the results may not be fully representative of the wider population, particularly in rural and underserved areas. In addition, the relatively small sample size may limit the generalizability of the findings, warranting cautious interpretation. For the future, studies with larger sample size that extends beyond the two hospitals and employs a recruitment strategy integrating both hospital-/clinic-based and community-focused approaches are recommended to validate these findings and uncover additional risk factors for typhoid-related complications.
Despite these limitations, the study has several strengths. It leverages laboratory-confirmed diagnoses from a well-defined surveillance program (SETA), enhancing diagnostic accuracy. The use of rigorous statistical methods also strengthens the reliability of the associations found between clinical complications and specific risk factors. Moreover, this study provides novel data on typhoid complications in Ghana, addressing a critical knowledge gap and offering evidence to inform public health interventions and clinical management strategies.
Conclusion
This study reveals a significant burden of disease complications among febrile patients, especially those with typhoid fever in Ghana. Treatment delays significantly increased the risk of typhoid complications, while the rural residence was independently associated with complications. In resource-limited settings, typhoid fever remains a critical cause of mortality. Given the similarity of typhoid fever symptoms with other febrile illnesses, it is appropriate for enhanced education on the infection with improved advocacy for early testing before treatment to tackle delays that will lead to a rise in related complications. Moreover, programmes should be targeted at urban communities to unravel the drivers of health-seeking behaviours concerning febrile conditions. Also, an enhanced focus on vaccines would be a strategic effort to prevent typhoid complications and reduce mortality.
Data Availability
The data underlying this study cannot be shared publicly due to consortium-level data governance and restrictions outlined in the data sharing policy of the Severe Typhoid in Africa (SETA) surveillance program. However, qualified researchers who meet the criteria for access to confidential data may request access from the Principal Investigator in Ghana via email at eowusu-dabo.chs@knust.edu.gh.
Acknowledgement
Special thanks to the EOD project team at Kwame Nkrumah University of Science in collaboration with the International Vaccine Institute for their support.
Supporting information
S1 Appendix. Data abstraction form
S2 Appendix. This file contains the output of the statistical data reduction techniques employed in this study
Competing interest
The authors declared that no competing interests exist.
Funding
This work was funded by the Bill & Melinda Gates Foundation (OPP1127988). The International Vaccine Institute (IVI) acknowledges its donors including the Republic of Korea and Swedish International Development Cooperation Agency. The funders had no role in the study design, data collection, data analysis, data interpretation, decision to publish, or preparation of the manuscript. The corresponding authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.