Articles

Mathematical modeling plays a central role in infectious disease epidemiology, shaping outbreak response strategies and informing public health policy. The COVID-19 pandemic demonstrated the value of these models but also exposed persistent limitations related to data fragility, lack of transparency, limited stakeholder engagement, and insufficient consideration of social and political contexts. Rather than critiquing modeling as a discipline, this perspective argues for a reorientation of infectious disease modeling toward a more responsive, equity-centered, and participatory paradigm. We propose a conceptual framework built on three interrelated principles: adaptability through real-time data integration, transparency via open-source and reproducible practices, and relevance through interdisciplinary and co-produced model design. Drawing on illustrative examples from COVID-19 and dengue control efforts, we highlight how integrating behavioral dynamics, local knowledge, and policy feedback can improve model usefulness and public trust. Reconceptualizing models as dynamic systems of inquiry rather than static forecasting tools can enhance decision-making and promote more equitable and effective responses to future public health emergencies.

This paper describes the current status of research on disease distress in elderly type 2 diabetic patients at home and abroad, with a view to developing targeted interventions for diabetic patients, improving self-management behavioral ability and quality of life in elderly type 2 diabetic patients, and improving patients' glycemic control.

Early-onset neurodegenerative diseases (EO-NDs), such as early-onset Alzheimer’s disease (EOAD), Parkinson’s disease (EOPD), and familial amyotrophic lateral sclerosis (fALS), often stem from monogenic causes and manifest before typical age thresholds. These disorders frequently feature disrupted mitochondrial function and heightened oxidative stress, which together accelerate neuronal damage and degeneration. In this work, the author performs a comprehensive analysis of the literature and data related to mitochondrial dysfunction and redox imbalance in EO-NDs. Bibliometric trends were assessed using R-based tools on PubMed datasets, highlighting keyword networks and publication surges in recent years. Publicly available RNA-seq datasets from GEO and SRA were examined, with example DESeq2 analysis illustrating altered mitochondrial gene expression in EO-ND patient-derived samples. Network modeling of redox pathways using Python’s networkx demonstrates how oxidative stress can propagate through metabolic networks. Together, these computational approaches reinforce that mitochondrial DNA mutations, impaired electron transport chain (ETC) function, and reactive oxygen species (ROS) accumulation play central roles in EO-ND pathogenesis. The discussion further evaluates why antioxidant clinical trials have largely failed and how emerging therapies such as gene replacement, antisense oligonucleotides, and mitochondrial biogenesis modulators may provide more effective interventions.

A man in his 60s with multiple vascular comorbidities presented with sudden, painless vision loss in one eye. Although he had a high risk for atherosclerotic events, initial evaluation for stroke was negative for acute ischemia, but found to have markedly elevated inflammatory markers. Accordingly, giant cell arteritis was investigated and Ophthalmologic findings and fulfillment of the 2022 American College of Rheumatology/European Alliance of Associations for Rheumatology classification criteria supported the diagnosis of giant cell arteritis, despite a negative temporal artery biopsy. Management included high-dose glucocorticoids and delayed tocilizumab initiation due to the need for multiple vascular surgeries. Vision loss was irreversible, but systemic symptoms resolved and vascular interventions were successful. This case highlights the diagnostic and management complexities of biopsy-negative giant cell arteritis in patients with severe atherosclerotic vascular disease, emphasizing the importance of clinical judgment and established classification criteria when imaging and biopsy results are inconclusive.

Avian influenza is a very lethal disease caused by influenza viruses that normally circulate among birds, and contains well-known subtypes are A(H5N1) and A(H7N9). Human infection is rare and occurs through close contact with infected poultry, therefore, confirming a history of such contact is important. The same treatment as for seasonal influenza is recommended, such as the neuraminidase inhibitors, cap endonuclease inhibitors, and RNA polymerase inhibitor. The avian influenza patients are regulated by the Infectious Diseases Control Law in Japan, we should manage the avian influenza appropriately.

This research is a collaboration involving a university team, a partnering corporation, and a hemodialysis clinic, which is a cross-disciplinary research initiative in the field of Artificial Intelligence of Things (AIoT) within the medical informatics domain. The research has two objectives: (1) The development of an <i>Internet of Things (IoT)</i><i>-based</i><i> Information System</i> customized for the hemodialysis machines at the clinic, including transmission bridges, clinical personnel dedicated web/app, and a backend server. The system has been deployed at the clinic and is now officially operational; (2) The research also utilized de-identified, anonymous data (collected by the officially operational system) to train, evaluate, and compare <i>Deep Learning-based Intradialytic Blood Pressure</i><i> (BP)</i><i>/Pulse </i><i>Rate (PR) </i><i>Predictive Models</i>, with subsequent suggestions provided. Both objectives were executed under the supervision of the Institutional Review Board (IRB) at Mackay Memorial Hospital in Taiwan. The system completed for objective one has introduced three significant services to the clinic, including automated hemodialysis data collection, digitized data storage, and an information-rich human-machine interface as well as graphical data displays, which replaces traditional paper-based clinical administrative operations, thereby enhancing healthcare efficiency. The graphical data presented through web and app interfaces aids in real-time, intuitive comprehension of the patients’ conditions during hemodialysis. Moreover, the data stored in the backend database is available for physicians to conduct relevant analyses, unearth insights into medical practices, and provide precise medical care for individual patients. The training and evaluation of the predictive models for objective two, along with related comparisons, analyses, and recommendations, suggest that in situations with limited computational resources and data, an Artificial Neural Network (ANN) model with six hidden layers, SELU activation function, and a focus on artery-related features can be employed for hourly intradialytic BP/PR prediction tasks. It is believed that this contributes to the collaborating clinic and relevant research communities.

Legionnaires' disease became widely known following an outbreak of pneumonia in the United States in 1976. It is often caused by infection from artificial water sources such as cooling towers, water supply and heating systems, and recirculating hot tubs. To effectively implement infection prevention measures for Legionnaires' disease, collaboration among healthcare workers, water supply and heating system managers, building hygiene personnel, and other relevant parties is essential. It is important to note that outbreaks of Legionnaires' disease continue to occur frequently both domestically and internationally. While the number of reported cases of Legionnaires' disease in Japan has increased, the mortality rate has decreased but has stabilized at a lower level. Caution is also required as reports have been made in association with disasters and travel, in addition to artificial environmental water.

Smoking is a well-documented risk factor of cardiovascular diseases (CVD) and premature death. Previous studies have focused on smoking duration and total cigarette consumption, but a 2024 paper by Li et al. highlights the time between waking up and smoking the first cigarette as a risk factor of mortality, noting that smoking ≤5 minutes after waking is strongly linked to a higher risk of mortality and a higher chance of incident myocardial infarction or stroke, and may be a sign of nicotine dependence. Another study by Hu et al. (2024) states that early-morning smoking more strongly correlates with incident type 2 diabetes than total cigarette consumption, adding to preceding evidence that early-morning smoking is linked to type 2 diabetes and chronic obstructive pulmonary disease (COPD). The demonstrated association with adverse health outcomes and early-morning smoking suggests delayed time to first cigarette can be a useful target as part of smoking interventions. These findings indicate the necessity of public health policies targeting smoking behaviour in addition to cessation as a way to decrease the associated disease burden.

<b>Background:</b> Minorities’ Diminished Returns (MDRs) theory posits that the health benefits of socioeconomic resources, such as education, are smaller for marginalized and minoritized populations, including immigrants. While MDRs have been extensively documented for racial and ethnic minorities, less is known about whether these diminished returns extend to immigrant populations. This study tested MDRs of education on various health and cognitive outcomes, including self-rated health (SRH), cognitive function, numeracy, number of chronic medical conditions, and limitations in activities of daily living (ADLs) among immigrants compared to non-immigrants in the United States. <b>Objective</b><b>. </b>To examine whether educational attainment confers weaker protective effects on SRH, cognitive function, numeracy, chronic medical conditions, and ADLs in immigrants compared to non-immigrants, confirming the presence of MDRs across these domains. <b>Methods</b><b>:</b><b> </b>We used data from the Understanding America Study (UAS), a nationally representative survey of U.S. adults. We tested the association between educational attainment and five outcomes—SRH, cognitive function, numeracy, number of chronic medical conditions, and limitations in ADLs—across immigrant and non-immigrant groups. Multivariate regression models were employed, adjusting for key sociodemographic covariates. <b>Results</b><b>:</b><b> </b>The protective effects of education on a range of health outcomes were significantly weaker for immigrants compared to non-immigrants. Education level showed weaker associations with SRH, cognitive function, numeracy, number of chronic conditions, and ADLs among immigrants. These findings suggest that even at higher levels of educational attainment, immigrants experience poorer health and cognitive functioning than their U.S.-born counterparts.<b> </b><b>Conclusion</b><b>:</b><b> </b>This study offers strong evidence for the MDRs of education on multiple health outcomes among U.S. immigrants. One possible explanation is that, despite achieving higher levels of education, immigrants often face structural barriers—such as discrimination, limited access to resources, and economic inequities—that constrain the health-related benefits typically associated with educational attainment. Additionally, a portion of immigrant education may be acquired outside the United States, where credentials may not be fully recognized or rewarded within the U.S. labor market. These findings highlight the importance of policies aimed at addressing systemic inequities and improving access to healthcare, employment opportunities, and social support for immigrant communities. Future research should further explore the mechanisms underlying these diminished returns and identify policy solutions to reduce their impact. <b>Keywords: </b>Educational Attainment, Immigrants, Nativity, Self-Rated Health, Chronic Disease, Activities of Daily Living (ADL), Cognitive Function

(1) <b>Background</b>: Psychological flexibility, the ability to adapt to changing demands while staying true to personal values, is linked to better health behaviors. However, its relationship with cardiovascular health behaviors, particularly in Filipino populations, remains underexplored. (2) <b>Aim</b>: This study aimed to examine the relationship between psychological flexibility and cardiovascular health behaviors among outpatients in Rizal, Philippines, focusing on BMI, smoking, physical activity, and dietary habits. (3) <b>Methods</b>: A cross-sectional, descriptive-correlational design was used with 100 outpatient participants from selected hospitals. Psychological flexibility was measured using the Acceptance and Action Questionnaire-II (AAQ-II), and cardiovascular health behaviors were assessed using a modified version of the American Heart Association’s Life Simple 7 tool. Descriptive statistics and Pearson’s correlation were applied. (4) <b>Results</b>: The findings showed that respondents had neutral levels of psychological flexibility. While most exhibited intermediate BMI and physical activity, dietary habits varied. A significant positive correlation was found between psychological flexibility and whole grain consumption. However, no significant associations were found with BMI, smoking, or physical activity. (5) <b>Conclusions</b>: Psychological flexibility appears to influence specific health behaviors, such as dietary choices, but does not strongly correlate with other cardiovascular health behaviors. Further research is needed to explore its broader role in cardiovascular disease prevention.

COVID-19 vaccines have demonstrated efficacy in reducing the prevalence of serious illnesses. The relative risk of hospitalization and mortality for patients who get breakthrough infections after immunization versus those who develop reinfections after a prior spontaneous infection is examined in this correspondence. Based on a study on U.S. Veterans who were not vaccinated and experienced reinfections had a much higher risk of experiencing severe illness outcomes compared to those who had received immunizations and experienced breakthrough infections, even if the rates of reinfection and breakthrough infection were similar. Our findings highlight the value of immunization in reducing severe COVID-19 outcomes, even in the presence of reinfections.

<b>Background</b>: Type 2 Diabetes Mellitus (T2DM) and Alzheimer’s Disease (AD) are increasingly linked through shared pathophysiological mechanisms, giving rise to the concept of Type 3 Diabetes Mellitus (T3DM). Brain insulin resistance, oxidative stress, and neuroinflammation are central to both conditions, contributing to cognitive decline and AD progression. <b>Aim:</b> This review aims to explore this emerging relationship and its implications for prevention and management. <b>Methods</b>: Using an integrative review, 21 studies were systematically analyzed. The review focused on identifying demographic, genetic, and lifestyle factors contributing to T2DM and AD and examined shared molecular pathways such as insulin dysregulation and amyloid-beta accumulation. <b>Results</b>: The findings reveal that T3DM shares key features with T2DM and AD, including insulin resistance and chronic inflammation. Lifestyle interventions, such as diet and exercise, alongside routine cognitive and metabolic screenings, are critical in mitigating progression. <b>Conclusions</b>: Further research into diagnostic biomarkers and targeted therapies is essential to manage T3DM and its impact on AD. The role of nursing professionals in early detection, education, and holistic management is emphasized as vital in addressing this dual disease burden. This review offers actionable insights into integrated strategies for addressing these interconnected conditions.

<b>Background:</b> Peripartum cardiomyopathy (PPCM) is a life-threatening heart muscle disease of unknown aetiology that affects women during the peripartum period, particularly in sub-Saharan Africa. While many studies have observed normal blood pressure (BP) in PPCM patients, none have explored whether their BP is appropriate for their body size. This study investigated the correlation between body anthropometric parameters and BP in PPCM patients, comparing the findings with those of age-matched normal peripartum controls. <b>Methods: </b>A cohort of 105 women, each from PPCM and matched normal peripartum control groups, were recruited from three healthcare facilities in Sokoto. Blood pressure (BP) parameters were assessed in relation to their anthropometric measurements, and the findings were compared between the two groups. <b>Results:</b> The PPCM patients were significantly smaller in body weight (57.0 ±11.6 Kg vs 66.8 ±13.8 Kg, P <.0001), body mass index (BMI) (21.9 ±4.1 Kg/m2 vs 25.4 ±5.4 Kg/m2, P <.0001, body surface area (BSA) (1.3 ±0.7 m2 vs 1.7 ±0.2 m2, P <.0001), Lean body mass (LBM) (45.3 ±7.0 Kg vs 49.4 ±4.1 Kg, P <.0001) and Percentage body fat (BF) (23.5 ±10.9 % vs 31.2 ±6.9 %, P <.0001). Similarly, PPCM patients had significantly higher systolic BP (SBP), Pulse pressure (PP) and Mean arterial blood pressure (MABP) compared to the normal peripartum PPCM control. Further, linear regression analysis showed that there was higher slope of the relationship between anthropometric indices and SBP and PP in the PPCM cohort, compared to the normal peripartum control group. A similar trend of the slope was seen in the Pearson’s coefficient of the relationship of the anthropometries and BP parameters. <b>Conclusions:</b> This study found that women with peripartum cardiomyopathy (PPCM) exhibited disproportionately higher systolic blood pressure (SBP) and pulse pressure (PP) for each unit increase in anthropometric measurements compared to normal peripartum controls. Notably, PPCM patients had significantly lower anthropometric measures, potentially attributable to poverty and chronic undernutrition. Additionally, the effects of poor antenatal care, lack of immunization and recurrent infection should be considered. These findings suggest an abnormal relationship between anthropometry and blood pressure in PPCM patients, which may have detrimental effects on their cardiovascular health. This abnormal relationship may contribute to the development of heart failure (HF) in PPCM patients and potentially increase the risk in women susceptible to PPCM. Even-though our assumption, yet to be proven. To address this concerning trend in vulnerable populations, improvements in nutritional status, socioeconomic determinants health, adequate antenatal care (ANC), immunization, and infection prevention should be considered.

<b>Background</b><b>:</b> Socioeconomic status (SES) is a well-established determinant of health, often associated with lower risk of cardiometabolic diseases (CMD). However, the extent to which SES influences CMD may vary by gender due to differences in social roles, health behaviors, and biological susceptibilities. This study examined the relationship between SES, measured by the poverty-to-income ratio (PIR), and CMD indicators—including obesity, diabetes, and cardiovascular disease (CVD)—among men and women using data from the National Health and Nutrition Examination Survey (NHANES). <b>Methods</b><b>:</b> This cross-sectional study utilized NHANES data (1999-2018), adjusting for race/ethnicity and age. SES was operationalized using PIR, with CMD outcomes (obesity, diabetes, and CVD) as dependent variables. Generalized linear models (GLM) were employed to evaluate the main effects of SES on CMD, with gender included as a moderator. <b>Results</b><b>:</b> Higher SES was associated with lower overall CMD risk. However, the protective effects of SES were more pronounced in women than in men for all outcomes. These findings suggest that gender-specific pathways may mediate the relationship between SES and CMD. Women may derive greater health benefits from higher SES due to factors such as reduced stress exposure, healthier behaviors, and increased healthcare utilization. Conversely, the weaker association observed in men may reflect differences in social hierarchy sensitivity, responses to unemployment, or other contextual factors. <b>Conclusion</b><b>:</b> The findings highlight the importance of gender-specific considerations when addressing SES-related disparities in CMD outcomes. Policies and interventions aimed at reducing CMD burden should account for these gender differences to promote equitable improvements in cardiometabolic health. Further research is needed to unravel the mechanisms driving these differences and to inform targeted strategies.

Over the past few decades, cardiovascular disease and related complications have surpassed all others as the important causes of death on a universal scale. At the moment, they are the important cause of mortality universal, including in India. It is important to know how to find cardiovascular problems early so that patients get better care and prices go down. This project utilizes the UCI Heart Disease Dataset to develop ML and DL models capable of detecting cardiac diseases. Heart illness was categorized using Convolutional Neural Network (CNN) models, which are able to detect intricate patterns in supplied data. A confusion matrix rating, an F1-score, a ROC curve, accuracy, precision, and recall were some of the measures used to grade the model. It did much better than the Neural Network, Deep Neural Network (DNN), and Gradient Boosted Trees (GBT) models, with 91.71% accuracy, 88.88% precision, 82.75% memory, and 85.70% F1-score. Comparative study showed that CNN was the most accurate model. Other models had different balances between accuracy and recall. The experiment results show that the optional CNN model is a decent way to identify cardiovascular disease. This means that it could be used in healthcare systems to find diseases earlier and treat patients better.

<b>Objective: </b>This study aims to investigate the relationship between the presence of chronic medical conditions and cessation among U.S. adults who use combustible tobacco. We hypothesized that having chronic medical conditions would be associated with a higher likelihood of successfully quitting combustible tobacco.<b> </b><b>Methods: </b>We utilized longitudinal data from the Population Assessment of Tobacco and Health (PATH) Study, using data from Waves 1 to 6. Only current daily smokers were included in our analysis. The independent variable was the number of chronic medical conditions, defined as zero, one, or two or more. The outcome was becoming a former smoker (quitting smoking). Using multivariate regression analyses, we assessed the association between the number of chronic conditions and tobacco cessation over the six waves. We controlled for potential confounding variables, including demographic factors and socioeconomic status.<b> </b><b>Results: </b>Our analysis revealed a significant association between the number of chronic medical conditions and the likelihood of quitting smoking. Specifically, individuals with two or more chronic conditions exhibited a greater probability of quitting smoking compared to those with no chronic conditions. The results remained significant after adjusting for potential confounders.<b> </b><b>Conclusions: </b>Multiple chronic medical conditions may act as a catalyst for smoking cessation among U.S. adults. This suggests that the presence of multimorbidity, defined as multiple chronic disease diagnoses, may serve as “teachable moments,” prompting significant health behavior changes. These findings highlight the potential for leveraging chronic disease management and healthcare interventions to promote tobacco cessation, particularly among individuals with multiple chronic conditions.

Intestinal malrotation is an embryological abnormality modifying the classic anatomy of the small and large bowels, particularly the topographical one. Inflammatory bowel disease (IBD) is characterised by anatomical lesions with preferential intestinal tropism. These two conditions are rarely associated. They represent a real diagnostic and therapeutic challenge due to the overlap of non-specific symptoms and the complexity of the clinical management. We report the case of a young woman presenting with a flare-up of her IBD and a partial common mesentery syndrome. Clinicians should be aware of the potential pitfalls of the two entities to propose the adequate therapeutic strategy regarding the full understanding of the anatomy, notably when surgery is needed.

This paper leverages gene and cell therapy research in diverse disorders ranging from monogenic to infectious diseases to cancer and emerging breakthroughs, where one can harness individual genes or a synthetic gene sequence designed based on a shared molecular pattern in infected cells to better fight various disorders [1]. A pivotal task is to predict the performances of candidate gene therapies to guide clinical translational research using methods such as retrospective bioinformatic analyses. Implementing them to a large-scale gene therapy database reveals that it is feasible to construct and apply well-performing interpretable, supervised learning models [2]. Preliminary evidence of machine learning approaches' statistical significance helps clinicians and biomedical researchers, market participants, and regulatory and economic experts derive relevant, practical applications, thereby enhancing the deployment of gene therapy and genomics to achieve positive, long-term growth for humanity while alleviating the ongoing worldwide economic burden precipitated by prolonged and recurring diseases. Deploying machine learning techniques to accelerate gene and cell therapy drug development and trials shall also mitigate the existing obstacle of limited patient access to emerging, transformative medical innovations such as gene therapy due to skyrocketing prices, which often herald gene therapy products as the world's most expensive medicines [3]. Moreover, in preventing patients from accessing effective, life-saving genetic medicines, there commonly exists a multidimensional access gap encompassing the availability, affordability, and quality or acceptability of these clinical treatments. The ensuing substantial gap has repeatedly been documented and mainly emanates from differential institutional and socio-political choices around resource allocation at international and domestic levels [4]. Particularly, it is also due to the stringent licensure and regulatory approval processes underpinned by insufficient evidence for novel safety and clinical efficacy profiles for genetic therapies in multiple micro-local diagnoses and subpopulations. We believe that a higher likelihood of gene therapy adoption shall result when the clinical evidence path contains adequate representation from the most diverse and relevant patient populations [5].

Cancer is the second cause of death worldwide, affecting one in six people, with breast cancer being the most prevalent in females. Adapting to an oncological disease entails many physical and psychological changes that affect the patient and their families. This work aims to present existing scientific research on adaptation to oncological disease and the end of life of women with metastatic cancer aged between 45 and 65, framing with Acceptance and Commitment Therapy. (TAC). Fifty documents with publication dates between 2002 and 2022 were included in this study. It was found that there is much information on the topic in question, as it is a problem that affects not only women but also all the systems they are in. When faced with a terminal diagnosis, a woman faces many doubts and uncertainties, in addition to all the physical effects of the disease. Therefore, she should be accompanied by a team specialized in Palliative Care, which can provide her and her family with all the support needed in this challenging phase.

Quantitatively, this study aimed to determine the abundance and diversity of the insect fauna that visits the staminate and pistillate flowers of <i>Cocos</i><i> nucifera.</i> The study was conducted at an experimental plantation belonging to the Coconut Research Programme (CRP) of the Oil Palm Research Institute (OPRI) of the Council for Scientific and Industrial Research (CSIR), to provide diagnostic support for the Cape St. Paul Wilt Disease (CSPWD) at Asebu in the Central Region of Ghana. The populations of coconut palms represented the dwarf type with few tall ecotypes. Five Insects were randomly chosen with newly opened inflorescences. Observations and collections of insect visitors to coconut flowers were made once a week on 30 newly opened inflorescences, five from each batch within the plantation. Specimens of the data were deposited in the official insect collection and processed at the laboratory of the Entomology Museum of the Department of Conservation Biology and Entomology, University of Cape Coast, Ghana. The study indicated that 9 different species of insects were identified to be the true fauna that visited the staminate and pistillate flowers of <i>C. </i><i>nucifera</i><i> </i><i>Ethiosciapus</i><i> sp., </i><i>Sarcophaga</i><i> sp., </i><i>Scolia</i><i> </i><i>dubia</i><i>, </i><i>Lucilia</i><i> sp., </i><i>Ornidia</i><i> sp., </i><i>Apis</i><i> </i><i>melifera</i><i>, </i><i>Dactylurina</i><i> </i><i>standingeri</i><i>,</i> Red Ant and Black Ant. These insects were observed in all the six batches considered and were available at all times of the day. Most of the insects were observed in the early morning from 6 am - 9 am followed by the evening 4 pm –7 pm. The abundance of insect visitors was low during the mid-day (11 a.m. to 3 p.m.) in all six batches during high temperatures. The results of this study revealed that there were abundances of <i>Ethioscipus</i><i> sp. </i>was the least abundant in all the batches followed by <i>Scolia</i><i> </i><i>dubia</i><i> </i>then <i>Sarcophaga</i><i> sp.</i> Red Ants had the highest abundance in most of the Batches thus becoming the most abundant insect that forage the coconut inflorescence at the Asebu plantation. The bees, <i>Apis</i><i> </i><i>melifera</i><i> </i>and<i> </i><i>Dactylurina</i><i> </i><i>standingeri</i><i> </i>were the most abundant species after the Red Ants. All these groups of insects were not considered in the study and it is recommended that further studies consider such visitors to observe which insects are doing what on the inflorescence. The range for the ‘time of day for’ of the study was mostly diurnal (morning 6 am-9 am, afternoon 11 am-2 pm and evening 4 pm7 pm). There was no observation made of the pollination system or activities of these insect visitors nocturnally. There may be high pollination activities of these insects during the late evenings. It is recommended that future work should incorporate the late evening period to observe an abundance of diurnal insect visitors of the coconut inflorescences.<b>Keywords: </b>Insect, Fauna, Staminate, Pistillate Flowers, <i>Cocos</i><i> nucifera</i>