Clinical and Epidemiological Characteristics of Chikungunya and Dengue Infections in Provincial Hospitals of Davao de Oro, Philippines

doi:10.21203/rs.3.rs-4904666/v1

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Clinical and Epidemiological Characteristics of Chikungunya and Dengue Infections in Provincial Hospitals of Davao de Oro, Philippines

https://doi.org/10.21203/rs.3.rs-4904666/v1

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Mosquito-borne diseases like dengue and chikungunya are endemic in the tropical region and is a common cause of acute febrile illness in both adults and children. The Philippines, home to over a hundred million residents and visited by several million tourists each year, is one such region where the risk of these diseases is endemic. To better understand the detailed situation, we estimated the proportion of these diseases in the community by conducting a prospective observational study conducted in four provincial hospitals of Davao de Oro, Philippines from February 2019 to February 2020. Serum from 382 study participant was used for laboratory confirmation of dengue or chikungunya either by antigen, antibody or by RT-PCR. Dengue was diagnosed in 57.1%, chikungunya 7.07%, co-infection with both dengue and chikungunya in 7.3%, and the etiology was undetermined in 35.9% of study participants. Common clinical symptoms included fever, headache, and rash, which were overlapping symptoms and clinically indistinguishable at presentation to the hospital, necessitating the need for laboratory diagnostics. The identification of the presence of chikungunya in Davao de Oro calls for increased awareness, improved diagnostics, and integrated disease control measures to manage outbreaks that can occur in dengue endemic regions.

acute febrile illness

chikungunya

dengue

coinfection

Southeast Asia

Philippines

Mosquito-borne viruses like dengue and chikungunya are frequent causes of acute febrile illnesses in Southeast Asia(1, 2). Dengue viruses are Orthoflavivirus genus and consist of four distinct serotypes (DENV 1–4), each containing multiple genotypes and offering transient cross-protective immunity(3). Chikungunya virus is an Alphavirus virus and has three genotypes, which includes the West African lineage, East, Central and South African (ECSA) lineage and an Asian lineage(4). During the initial presentation at the hospital, distinguishing between the two diseases can be challenging, as they manifest overlapping symptoms. Laboratory tests, such as antigen or antibody assays, or PCR, are necessary for a definitive diagnosis(5).

However, the clinical trajectories of both diseases differ greatly. In dengue, the majority of patients remain asymptomatic, and those who do develop symptoms typically experience a self-limited illness. In some cases, symptoms may include bleeding, plasma leakage, and shock(6). On the other hand, in chikungunya, the majority of patients develop symptoms characterized by arthralgia and arthritis(7). The clinical course is also much longer, with symptoms of arthritis persisting for several months(8).

In the Philippines, cases of chikungunya and dengue have been reported since the late 1950s. Dengue has remained a major public health problem in the country, and the growing magnitude of the disease prompted the government to provide free diagnostics for dengue to locals under the national insurance scheme(9). This facilitates large-scale screening of patients presenting to hospitals with acute febrile illness to determine whether they have dengue. Due to the significant disease burden, the Philippines was also the first country in Asia to approve and provide dengue vaccine.

In contrast, chikungunya has not garnered as much public health interest, despite evidence of its presence(10, 11). This disparity may be due to the significant higher mortality rates associated with dengue compared to chikungunya. However, chikungunya tends to result in more severe long-term effects, impacting daily activities, causing loss of workdays, and leading to increased unproductiveness(8). A prospective cohort study in Cebu, Philippines, reported a rate of 3 symptomatic chikungunya infections per 100,000 person-years at the end of one year into the outbreak, they also further reported that outbreaks lasted three years(12).

The Philippines, composed of 81 provinces, includes Davao de Oro, comprises 11 municipalities, has a population of approximately 767,547 people and features four secondary provincial hospitals located in Montevista, Laak, Pantukan, and Maragusan. Davao de Oro is home to migrants from Luzon and Visayas, as well as ethnic tribes such as the Mansaka, Mandaya, Davaoeno, and Kalagan. The main sources of income in the area are business establishments, banana plantations, and vast silver and gold mines across the province.

Chikungunya is likely under-reported in this area due to several reasons. Unlike dengue, which benefits from free diagnostic tests provided by the government to registered Filipinos under national insurance schemes, diagnostic tests for chikungunya are not widely available. Many residents, particularly migrants and their families working in the agriculture and mining sectors of Davao de Oro, may not be registered in the national insurance scheme and therefore lack access to diagnostics. This gap in access to diagnostics could contribute to the under-diagnosis and under-reporting of chikungunya in this region. Understanding the true prevalence of chikungunya in this context is crucial for implementing effective public health strategies and improving healthcare access for all residents of Davao de Oro. In this study, we aimed to estimate the proportion of acute chikungunya and dengue infection among patients with acute febrile illness in four provincial hospitals of Davao de Oro in the Davao region.

This multi-center, prospective study was conducted at four provincial hospitals in Davao de Oro province, located in the southeastern part of the Davao region (see Supplementary Materials, Figure S1). The hospitals included in the study were Montevista Provincial Hospital, Laak Provincial Hospital, Pantukan Provincial Hospital, and Maragusan Provincial Hospital. Patients between the ages of 1 to 65 years who presented to the emergency department with complaints of fever or had experienced at least one episode of fever of 38.5°C or higher within the past week and suspected dengue infection were recruited to the study. Blood samples were collected by venipuncture, and serum was separated by centrifugation and stored at -80°C until analysis.

1.1 Dengue NS1 antigen and IgM/IgG antibody assay

A lateral flow rapid point-of-care diagnostic test kit for dengue, manufactured by Chembio Diagnostics, Inc. (NY, USA), was used to detect the dengue NS1 antigen and anti-dengue virus IgM and IgG antibodies. The tests were performed according to the manufacturer's instructions, using 10µL of serum. Results were interpreted 15 minutes after the test was conducted. The test was considered positive if two bands appeared, indicating the presence of NS1 antigen and IgM, along with the control band. If no bands appeared, the test was considered negative. The appearance of IgG alone with the control band indicated a previous infection. If the control band failed to appear, the test was deemed invalid.

1.2 Chikungunya IgM antibody assay

To evaluate the presence of anti-chikungunya virus IgM antibodies in this study, we utilized a commercially available indirect enzyme linked immunosorbent assay, EUROIMMUN, Lübeck, Germany. The assay was performed in accordance with the manufacturer’s instructions as singlicates. In brief, 10µL of serum was diluted with the buffer solution provided by the manufacturer and added into a pre-coated 96 well microplate with a serum dilution of 1:100. Following this the microplate underwent three wash cycles with a working strength wash buffer, and the antibodies were identified by the addition of an enzyme conjugate (peroxidase-labelled anti-human IgM). Subsequently, a substrate solution containing THM/H₂O₂ was added to induce the development of a blue color. The process was halted by the addition of 0.5M sulfuric acid, and the photometric measurement was recorded at a wavelength of 450 nm. The optical density was used to quantify the concentration of specifically anti-chikungunya virus antibodies present in the serum samples. Results were evaluated through a semiquantitative approach, calculating a ratio of the extinction of the patient serum sample over the extinction of the calibrator. This ratio was interpreted as follows as < 0.8 negative, >=0.8 to < 1.1 borderline and > = 1.1 as positive.

1.3 RNA extraction and Reverse Transcription Polymerase Chain Reaction for Chikungunya.

Viral RNA was extracted from 150uL of serum using an RNA extraction kit (Bioneer AccuPrep® viral RNA extraction kit, Daejeon,Korea) according to the manufacturer’s instruction. Quantification of CHIKV genomes was conducted using the TaqMAn quantitative real-time RT PCR method employing specific primers and a probe designed to target the 1200 bp region of the Nsp1 gene of CHIKV, as detailed in a previous study (ref. PMID:36016427)

A standard curve was drawn using CHIKV RNA that was prepared from a CHIKV strain TM009_2009 (ON406426). The standard curve was prepared from six dilutions containing 10¹ to 10⁶ PFU/mL, and the detection limit was determined to be about 10² PFU/mL.

1.4 Reverse Transcription Polymerase Chain Reaction for Dengue

A previously described techniques for RNA quantification, which was performed using a One-Step SYBR® Prime Script RT-PCR Kit II from Takara Bio Inc. (Kusatsu, Japan). cDNA synthesis from RNA was carried out using reverse transcriptase Prime Script RTase, and polymerase chain reaction amplification was conducted with TaKaRa Ex Taq HS(13).

1.5 Statistical analysis

A One-way ANOVA was used to assess parametric variables across multiple groups such as days of fever and haematocrit level, while the Mann-Whitney U-test was employed to evaluate differences in nonparametric variables between groups such as age, WBC and Platelete. The chi-square test was utilized to assess categorical variables, and Fisher's exact test was applied specifically when more than 20% of cells had expected frequencies less than 5.A P-value of less than 0.05 was considered significant for all tests performed. All statistical analyses were conducted using Microsoft Excel and STATA version 17 for MacOS 14.5 (23F79).

Over a 14-month study period, 382 patients were screened for chikungunya and dengue at four provincial hospitals in Davao de Oro, Philippines. Amongst these cases identified as acute febrile undifferentiated illness, 27 (7.07%) tested positive for circulating anti-chikungunya IgM, 190 (49.74%) tested positive for dengue infection, with the detection of both dengue NS1 antigen and anti-dengue IgM antibody. Additionally, 28 (7.33%) were identified as co-infected with both chikungunya and dengue, as their serum tested positive for anti-chikungunya IgM and also showed positive results for dengue NS1 and anti-dengue IgM. The remaining 137 cases (35.86%) had undetermined infectious etiologies, as both dengue and chikungunya were excluded as shown in Fig. 1.

3.1 Demographic and Epidemiological Characteristics

The age distribution varied significantly between the two diseases (p = 0.057), with median ages of 12 years for chikungunya and 17.5 years for dengue. Similarly, the median age was 17 years for cases identified as co-infected and for those who tested negative for both dengue and chikungunya, where the infective etiology remained unknown. The gender distribution, male: female across infection groups was as follows: chikungunya (9:18), dengue (103:87), co-infection (14:14), and unknown etiology (80:57). Although there appeared to be a higher proportion of females with chikungunya compared to dengue.

3.2 Hematological profile of the study cohort

The mean hematocrit levels were similar across groups, ranging from 40.7–43.3%.

Leukocyte count showed significant differences among groups (p = 0.0046). The median leukocytes were lowest in cases with co-infections 3.3 x10³ per microliter, with a range of 1.3 to 8.7 x10³/uL in cases with dengue infection the leukocytes mean was 3.7x10³/all, and in cases with chikungunya infection (4.05x x10³/all. In the group where the etiology was undetermined the mean leukocytes was 4.5x10³/µL. The median platelet counts were lowest in dengue infections (119 x 10^9/L, range: 30–395), followed by mixed infections (122 x 10^9/L, range: 40–255), unknown cases (126 x 10^9/L, range: 40–413), and highest in chikungunya infections (144 x 10^9/L, range: 90–332). This trend aligns with the known association between dengue and thrombocytopenia, while suggesting that chikungunya may have less impact on platelet counts. count also showed notable, though not statistically significant, variations among groups (p = 0.0511).

3.3 Clinical Manifestations of Chikungunya, Dengue and Febrile cases with Undetermined Etiology

Fever was the most prevalent symptom across all infection groups, affecting all cases. The mean duration of fever was also similar, ranging from 3.5 to 3.7 days (p = 0.7). Headache was another common symptom, affecting 66.7% of chikungunya patients, 73.2% of dengue patients, 75% of patients with co-infections, and 67.1% of unknown cases (p = 0.6). Retroorbital pain, often associated with dengue fever, showed no significant differences among groups (p = 0.50), ranging from 7.9% in dengue to 14.8% in chikungunya cases.

Musculoskeletal symptoms also varied among groups. Arthralgia was more prevalent in chikungunya (44.4%) and co-infections (42.9%) compared to dengue (32.6%) and unknown cases (29.9%) (p = 0.33). Myalgia, however, showed similar prevalence across groups (32.1% − 37.0%, p = 0.98).

Gastrointestinal symptoms showed some variations among groups. Nausea was more common in co-infections (78.6%) compared to other groups (p = 0.19), while vomiting followed a similar pattern: mixed (64.3%), dengue (53.7%), chikungunya (44.4%), and unknown (46%) (p = 0.22). Interestingly, diarrhea was relatively uncommon, with the highest prevalence in the unknown group (11%) and lowest in chikungunya (3.7%) (p = 0.214). Abdominal pain was most frequent in dengue infections (61.6%) compared to other groups (p = 0.087), potentially indicating a more severe gastrointestinal involvement in dengue cases.

Neurological involvement, represented by confusion, was rare across all groups. However, it was slightly more prevalent in chikungunya (3.7%) and co-infections (3.6%) compared to dengue (0.5%) and cases with unknown etiology (0%) (p = 0.072).

Rash was more common in chikungunya (59.3%) and dengue (63.7%) infections compared to co-infections (28.6%) (p = 0.052).

3.4 Distribution proportion of cases presenting to Provincial Hospitals.

The distribution of cases among the four provincial hospitals showed statistically significant differences (p = 0.018). Laak Provincial Hospital reported relatively even distribution infection of cases across types, with 37% of chikungunya cases, 29.5% of dengue cases, 28.6% of co-infections, and 29.2% of unknown cases with that of Pantukan Provincial hospital, with 37.0% of chikungunya cases, 27.4% of dengue cases, higher rate on co-infections at 46.4%. and 25.6% of unknown cases. Maragusan Provincial Hospital had a notably lower proportion of chikungunya cases (14.8%) compared to dengue (3.2%) and no co-infections. Montevista Provincial Hospital, in contrast, had a higher proportion of dengue cases (40%) compared to chikungunya (11.1%) and co-infections (25%), as shown in Table 1

Table 1

Comparison of Disease Groups in the study cohort.
Patient cohort, n = 382	CHIKV + ve n = 27	DENV + ve n = 190	CHIKV + ve DENV + ve n = 28	CHIKV -ve DENV -ve n = 137	P value
Laak Provincial Hospital	37.0%	29.5%	28.6%	29.2%	0.018
Maragusan Provincial Hospital	14.8%	3.2%	0%	6.6%
Montevista Provincial Hospital	11.1%	40%	25%	38.7%
Pantukan Provincial Hospital	37.0%	27.4%	46.4%	25.6%
Fever > 38.5^oC	100%	100%	100%	100%	N/A
Day of illness	3.7 ± 1.3	3.7 ± 1.3	3.6 ± 1.7	3.5 ± 1.4	0.700
Age	12 (1–49)	18 (0–65]	17 [0–43]	17 [0–65]	0.057
Gender ratio, male:female	9:18	103:87	14:14	80:57	0.117
Headache	66.7%	73.2%	75%	67.1%	0.605
Retroorbital pain	14.8%	7.9%	14.3%	10.9%	0.503
Arthralgia	44.4%	32.6%	42.9%	29.9%	0.334
Myalgia	37.0%	34.2%	32.1%	35.0%	0.982
Nausea	51.9%	63.7%	78.6%	60.6%	0.194
Vomiting	44.4%	53.7%	64.3%	46%	0.224
Diarrhea	3.7%	10%	0	11%	0.228
Abdominal pain	37.0%	61.6%	39.3%	37.2%	0.087
Rash	59.3%	63.7%	28.6%	49.6%	0.052
Confusion	3.7%	0.5%	3.6%	0	0.072
Hematocrit %	40.7 ± 5.5	42.5 ± 5.7	41.0 ± 4.0	43.3 ± 5.4	0.058
Neutrophils %	0.59 ± 0.19	0.52 ± 0.17	0.41 ± 0.22	0.51 ± 0.18	0.036
Lymphocytes %	0.385 (0.07–0.99)	0.33 (0.07–0.8)	0.41 (0.1–0.82)	0.36 (0.05–0.78)	0.371
Leukocytes x10³/uL	4.05 (2.1–9.2)	3.7 (1.4–19.5)	3.3 (1.3–8.7)	4.5 (1.7–19.4)	0.004
Platelets x10³/uL	144 (90–332)	119 (30–395)	122 (40–255)	126 (40–413)	0.051
Dengue NS1	0%	71.05%	92.86%	0%	0000
Anti-chikungunya IgM	100%	0%	100%	0%	0.000
Anti-dengue IgM	0%	51.58%	46.43%	0%	0.000
Anti-dengue IgG	59.26%	48.42%	39.29%	67.88%	0.001
Chikungunya RT-PCR	0.52%	0	0.52	0	N/A
Dengue RT-PCR	0	56.54%	0	42.41	N/A

Age is provided as median with maximum and the minmum range, while all other continuous variables are provided as Mean ± SD. P value was determined at < 0.005. Chi-square analysis was used for catergorical compasion of symptoms and Mann Whitney non-parametric test for continous variables.

4.1 Proportion of Chikungunya and Dengue in study cohort

Our results demonstrate that among patients presenting with acute febrile illness in Davao de Oro, dengue remains the predominant arboviral infection, accounting for 49.74% of cases. However, the detection of chikungunya in 7.07% of cases, along with 7.33% co-infections, highlights the emergence of chikungunya as a significant concern in the region. This proportion has previously not been reported in this region as in some areas of the Philippines(14). This findings from Davao de Oro suggest that chikungunya may be more widespread than currently recognized.

Furthermore, co-infections present a unique challenge in terms of diagnosis, clinical management, and potential disease severity. It has been previously reported that global pooled prevalence of dengue and chikungunya coinfection is 2.5% (95% CI: 1.8–3.4). To our knowledge there is no specific data about prevalence of co-infection in the Philippines prior this study. Nevertheless, co-infection from Asia, as a region, has the highest coinfection prevalence at 3.3% (95% CI: 2.3–4.6)(15). Our results suggest that co-infected patients may exhibit overlapping of symptoms characteristic of both viral infections, potentially complicating clinical assessment, and management.

However, one-third of cases (35.86%) where neither chikungunya nor dengue and the infective etiology remained undetermined. Here, we postulate this group of cases might have other Orthoflaviviruses such as Zika virus, Japanese encephalitis virus(16, 17). As these viruses remain endemic in the region, should be considered in the differential diagnosis for an arboviral infection in Southeast Asia.

Among other viral etiologies to consider, stratified according to age groups—children, adolescents, and adults—are DNA viruses such as human herpesviruses 4 and 5, which can present as mononucleosis, and HHV6, HHV7, or parvovirus B19, which can manifest as erythema infectiosum(18). Children and adolescents may be at risk of these infections. Other RNA viruses to consider in patients with febrile exanthema and enanthema include measles, rubella, and HIV(19–21). If there has been exposure to insects such as ticks or sick domestic animals, and all the above possibilities have been ruled out, we also suggest to screen for the Severe Fever with Thrombocytopenia Syndrome Virus (SFTSV) or bacterial illnesses such as rickettsiosis, leptospirosis, and salmonellosis(22–24). This plethora of pathogens reflects the complexity of diagnosing acute febrile illnesses in tropical regions, emphasizing the need for broader diagnostic capabilities to identify other potential pathogens causing similar clinical presentations(25).

4.2. Clinical Manifestations and Hematological Profile of Chikungunya and Dengue

The overlap in clinical symptoms between chikungunya and dengue infections poses a significant challenge for differential diagnosis based on clinical findings at presentation alone. Our study found that fever, headache, and myalgia were common across all groups, consistent with previous reports(2). The higher prevalence of arthralgia in chikungunya (44.4%) and co-infected cases (42.9%) compared to dengue (32.6%) aligns with the characteristic joint pain associated with acute chikungunya infection(7). This finding highlights the importance of considering chikungunya in cases presenting as acute febrile illness with prominent joint pain, especially with articular tenderness and peripheral joint involvement(8). Arthralgia can be exhibited with contagions we have described above. For example, rubella infection in adults can involve polyarthralgia of large joints, and similar clinical manifestations or arthropathy are also reported in adults with parvovirus B19.

Interestingly, our study found a higher prevalence of rash in both chikungunya (59.3%) and dengue (63.7%) cases compared to co-infections (28.6%). While rash is a known feature of both infections, the lower prevalence in co-infections is unexpected. Nevertheless, febrile rash might be missed without careful physical examination. Especially blanchable rashes associated with arboviral infections(26).

Dengue warning signs, such as abdominal pain, were observed more frequently in dengue cases (61.6%) compared to chikungunya (37.0%) and co-infections (39.3%). In resource-limited settings where dengue rapid diagnostics are unavailable, a clinical diagnosis can be made by considering the epidemiology, symptoms, and warning signs. Warning signs like abdominal pain are very useful in monitoring the clinical trajectory of suspected dengue cases, allowing for effective patient triage and prompt management(5).

In addition to identifying warning signs, the hematological profile can be used to monitor the progression of the disease. Specifically, in dengue, the hematological profile reflects dynamic bone marrow suppression, resulting in leukopenia. Leukocyte counts are among the first indicators to increase during recovery. Significantly lower leukocyte counts in dengue and co-infected cases, compared to chikungunya and cases of unknown etiology, are consistent with the known leukopenia associated with dengue infection(5).

The trend towards lower platelet counts in dengue and co-infected cases, although not statistically significant, is consistent with the thrombocytopenia commonly observed in dengue(5). The relatively higher platelet counts in chikungunya cases suggest that severe thrombocytopenia is less likely in chikungunya infection, which could be a useful distinguishing feature in clinical settings(2).

4.3 Distribution Chikungunya and Dengue in Provincial Hospitals of Davao de Oro

The significant differences in case distribution among the four provincial hospitals highlight the importance of considering local epidemiological patterns in arboviral disease surveillance and control.The higher proportion of chikungunya cases in Laak Provincial Hospital and Pantukan provincial Hospital for instance, suggests a potential localized outbreak or environmental factors favoring chikungunya transmission in that area. Conversely, the higher proportion of dengue cases in Montevista Provincial Hospital indicates that dengue remains the dominant arboviral threat in some parts of the region. Furthermore, these findings suggest that chikungunya may be significantly underreported in Davao de Oro. The lack of routine diagnostic testing for chikungunya, combined with its clinical similarity to dengue, likely contributes to underdiagnosis and underreporting. This situation is exacerbated by the focus on dengue in national health programs, including the provision of free dengue diagnostics under the national insurance scheme(9).

The high proportion of cases with undetermined etiology (35.86%) underscores the diagnostic challenges in resource-limited settings, impacting patient management and hindering disease surveillance and public health planning. The co-circulation of chikungunya and dengue viruses in Davao de Oro necessitates enhanced surveillance through comprehensive arboviral programs, improved access to diagnostic tests, and clinical education to distinguish between chikungunya and dengue.

Dengue in Davao de Oro maybe the leading arboviral infection (49.74%), amongst patients with acute undifferentiated febrile illness. The presence of chikungunya, previously underreported, suggests a wider circulation of arboviral infection in Davao de Oro. The variations in case distribution across hospitals reflects the need for localized surveillance and improved diagnostics to enhance public health strategies in endemic regions like the Philippines.

CHIKV Chikungunya Virus

DENV Dengue Virus

RT-PCR Real-time reverse transcriptase-polymerase chain reaction

SFTSV Severe Fever with Thrombocytopenia Syndrome Virus

Ethics approval and consent to participate: This study was conducted in accordance with the Declaration of Helsinki, and the Ethics Committee of the Faculty of Tropical Medicine, Mahidol University approved the protocol (Certificate of Approval No. MUTM 2019-015-01, February 25,2019) and approved by the Ethics Review Committee of the Compostela Valley Provincial Hospital Montevista, Davao de Oro Province (Case 005, January 25,2019). Informed consent was obtained from all study participants in the study as well as their written permission to publish this paper.

Consent for publication: All authors have read and agreed to the published version of the manuscript.

Availability of data and material: The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy of study participants.

Competing interests: The authors declare no conflicts of interest.

Funding: This research was funded by Mahidol Norway Capacity Building Initiative for ASEAN and Mahidol University Faculty of Clinical Tropical Medicine.

Authors' contributions – Conceptualization, NAJ; KB; LTB, CJS; VL; BP; WP and PC methodology, NAJ; KB; LTB, CJS; VL; BP; WP and PC validation, NAJ; KB; AP, PLA, and PC formal analysis, NAJ; KB; BP; AP.; PLA and PC; investigation, NAJ; KB; LTB, CJS and PC; resources, NAJ; KB; LTB, CJS and PC data curation, NAJ; KB; AP, PLA writing—original draft preparation, NAJ; AP, HAI; and PC writing—review and editing, NAJ; KB; LTB, CJS; AP, PAL; HAI; VL; WP and PC supervision, PC; and WP; project administration, NAJ; KB; LTB, CJS and PC; funding acquisition, PC.

Acknowledgements: The authors are grateful to all the study participants who volunteered to be part of this important study, which is part of the author’s doctoral thesis. The authors would also like to express their sincere appreciation and thank all the staff at the four Provincial Hospitals in Davao de Oro who are taking care and comforting patients in these four hospitals. Special thanks to Udomsak Silachamroon, whose fostering of an environment of academic excellence and encouragement greatly influenced the publication of this report.

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No competing interests reported.

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Clinical and Epidemiological Characteristics of Chikungunya and Dengue Infections in Provincial Hospitals of Davao de Oro, Philippines

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Abstract

Figures

1. Introduction

2. Materials and Methods

1.1 Dengue NS1 antigen and IgM/IgG antibody assay

1.2 Chikungunya IgM antibody assay

1.3 RNA extraction and Reverse Transcription Polymerase Chain Reaction for Chikungunya.

1.4 Reverse Transcription Polymerase Chain Reaction for Dengue

1.5 Statistical analysis

3. Results

3.1 Demographic and Epidemiological Characteristics

3.2 Hematological profile of the study cohort

3.3 Clinical Manifestations of Chikungunya, Dengue and Febrile cases with Undetermined Etiology

3.4 Distribution proportion of cases presenting to Provincial Hospitals.

4. Discussion

4.1 Proportion of Chikungunya and Dengue in study cohort

4.2. Clinical Manifestations and Hematological Profile of Chikungunya and Dengue

4.3 Distribution Chikungunya and Dengue in Provincial Hospitals of Davao de Oro

5. Conclusions

Abbreviations

Declarations

References

Additional Declarations

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