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1.
PLoS One ; 17(4): e0265820, 2022.
Article in English | MEDLINE | ID: covidwho-1779758

ABSTRACT

INTRODUCTION: The rapid expansion of the novel SARS-CoV-2 virus has raised serious public health concerns due to the possibility of misdiagnosis in regions where arboviral diseases are endemic. We performed the first study in northern Peru to describe the detection of SARS-CoV-2 IgM antibodies in febrile patients with a suspected diagnosis of dengue and chikungunya fever. MATERIALS AND METHODS: A consecutive cross-sectional study was performed in febrile patients attending primary healthcare centers from April 2020 through March 2021. Patients enrolled underwent serum sample collection for the molecular and serological detection of DENV and CHIKV. Also, serological detection of IgM antibodies against SARS-CoV-2 was performed. RESULTS: 464 patients were included during the study period, of which (40.51%) were positive for one pathogen, meanwhile (6.90%) presented co-infections between 2 or more pathogens. The majority of patients with monoinfections were positive for SARS-CoV-2 IgM with (73.40%), followed by DENV 18.09% and CHIKV (8.51%). The most frequent co-infection was DENV + SARS-CoV-2 with (65.63%), followed by DENV + CHIKV and DENV + CHIKV + SARS-CoV-2, both with (12.50%). The presence of polyarthralgias in hands (43.75%, p<0.01) and feet (31.25%, p = 0.05) were more frequently reported in patients with CHIKV monoinfection. Also, conjunctivitis was more common in patients positive for SARS-CoV-2 IgM (11.45%, p<0.01). The rest of the symptoms were similar among all the study groups. CONCLUSION: SARS-CoV-2 IgM antibodies were frequently detected in acute sera from febrile patients with a clinical suspicion of arboviral disease. The presence of polyarthralgias in hands and feet may be suggestive of CHIKV infection. These results reaffirm the need to consider SARS-CoV-2 infection as a main differential diagnosis of acute febrile illness in arboviruses endemic areas, as well as to consider co-infections between these pathogens.


Subject(s)
COVID-19 , Chikungunya Fever , Chikungunya virus , Coinfection , Dengue Virus , Dengue , Zika Virus Infection , Antibodies, Viral , Arthralgia , COVID-19/diagnosis , COVID-19/epidemiology , Chikungunya Fever/diagnosis , Chikungunya Fever/epidemiology , Coinfection/diagnosis , Coinfection/epidemiology , Cross-Sectional Studies , Dengue/diagnosis , Dengue/epidemiology , Fever/diagnosis , Humans , Immunoglobulin M , Peru/epidemiology , SARS-CoV-2 , Zika Virus Infection/epidemiology
2.
BMC Public Health ; 22(1): 667, 2022 Apr 06.
Article in English | MEDLINE | ID: covidwho-1779627

ABSTRACT

INTRODUCTION: The COVID-19 pandemic placed an unprecedented overload on healthcare system globally. With all medical resources being dedicated to contain the spread of the disease, the pandemic may have impacted the burden of other infectious diseases such as dengue, particularly in countries endemic for dengue fever. Indeed, the co-occurrence of COVID-19 made dengue diagnosis challenging because of some shared clinical manifestations between the two pathogens. Furthermore, the sudden emergence and novelty of this global public health crisis has forced the suspension or slow-down of several research trials due to the lack of sufficient knowledge on how to handle the continuity of research trials during the pandemic. We report on challenges we have faced during the COVID-19 pandemic and measures that were implemented to continue the iDEM project (intervention for Dengue Epidemiology in Malaysia). METHODS: This randomized controlled trial aims to assess the effectiveness of Integrated Vector Management (IVM) on the incidence of dengue in urban Malaysia by combining: targeted outdoor residual spraying (TORS), deployment of auto-dissemination devices (ADDs), and active community engagement (CE). Our operational activities started on February 10, 2020, a few weeks before the implementation of non-pharmaceutical interventions to contain the spread of COVID-19 in Malaysia. RESULTS: The three main issues affecting the continuity of the trial were: ensuring the safety of field workers during the interventions; ensuring the planned turnover of TORS application and ADD deployment and services; and maintaining the CE activities as far as possible. CONCLUSIONS: Even though the pandemic has created monumental challenges, we ensured the safety of field workers by providing complete personal protective equipment and regular COVID-19 testing. Albeit with delay, we maintained the planned interval time between TORS application and ADDs services by overlapping the intervention cycles instead of having them in a sequential scheme. CE activities continued remotely through several channels (e.g., phone calls and text messages). Sustained efforts of the management team, significant involvement of the Malaysian Ministry of Health and a quick and smart adaptation of the trial organisation according to the pandemic situation were the main factors that allowed the successful continuation of our research. TRIAL REGISTRATION: Trial registration number: ISRCTN-81915073 . Date of registration: 17/04/2020, 'Retrospectively registered'.


Subject(s)
COVID-19 , Dengue , COVID-19/epidemiology , COVID-19 Testing , Dengue/epidemiology , Dengue/prevention & control , Humans , Malaysia/epidemiology , Pandemics/prevention & control
3.
Sci Rep ; 12(1): 5459, 2022 Mar 31.
Article in English | MEDLINE | ID: covidwho-1768857

ABSTRACT

The recent increase in the global incidence of dengue fever resulted in over 2.7 million cases in Latin America and many cases in Southeast Asia and has warranted the development and application of early warning systems (EWS) for futuristic outbreak prediction. EWS pertaining to dengue outbreaks is imperative; given the fact that dengue is linked to environmental factors owing to its dominance in the tropics. Prediction is an integral part of EWS, which is dependent on several factors, in particular, climate, geography, and environmental factors. In this study, we explore the role of increased susceptibility to a DENV serotype and climate variability in developing novel predictive models by analyzing RT-PCR and DENV-IgM confirmed cases in Singapore and Honduras, which reported high dengue incidence in 2019 and 2020, respectively. A random-sampling-based susceptible-infected-removed (SIR) model was used to obtain estimates of the susceptible fraction for modeling the dengue epidemic, in addition to the Bayesian Markov Chain Monte Carlo (MCMC) technique that was used to fit the model to Singapore and Honduras case report data from 2012 to 2020. Regression techniques were used to implement climate variability in two methods: a climate-based model, based on individual climate variables, and a seasonal model, based on trigonometrically varying transmission rates. The seasonal model accounted for 98.5% and 92.8% of the variance in case count in the 2020 Singapore and 2019 Honduras outbreaks, respectively. The climate model accounted for 75.3% and 68.3% of the variance in Singapore and Honduras outbreaks respectively, besides accounting for 75.4% of the variance in the major 2013 Singapore outbreak, 71.5% of the variance in the 2019 Singapore outbreak, and over 70% of the variance in 2015 and 2016 Honduras outbreaks. The seasonal model accounted for 14.2% and 83.1% of the variance in the 2013 and 2019 Singapore outbreaks, respectively, in addition to 91% and 59.5% of the variance in the 2015 and 2016 Honduras outbreaks, respectively. Autocorrelation lag tests showed that the climate model exhibited better prediction dynamics for Singapore outbreaks during the dry season from May to August and in the rainy season from June to October in Honduras. After incorporation of susceptible fractions, the seasonal model exhibited higher accuracy in predicting outbreaks of higher case magnitude, including those of the 2019-2020 dengue epidemic, in comparison to the climate model, which was more accurate in outbreaks of smaller magnitude. Such modeling studies could be further performed in various outbreaks, such as the ongoing COVID-19 pandemic to understand the outbreak dynamics and predict the occurrence of future outbreaks.


Subject(s)
COVID-19 , Dengue , Bayes Theorem , Dengue/epidemiology , Disease Outbreaks , Humans , Markov Chains , Pandemics
5.
PLoS Negl Trop Dis ; 16(2): e0010134, 2022 02.
Article in English | MEDLINE | ID: covidwho-1753179

ABSTRACT

BACKGROUND: Dengue virus (DENV) infection may be associated with increased risks of major adverse cardiovascular effect (MACE), but a large-scale study evaluating the association between DENV infection and MACEs is still lacking. METHODS AND FINDINGS: All laboratory confirmed dengue cases in Taiwan during 2009 and 2015 were included by CDC notifiable database. The self-controlled case-series design was used to evaluate the association between DENV infection and MACE (including acute myocardial infarction [AMI], heart failure and stroke). The "risk interval" was defined as the first 7 days after the diagnosis of DENV infection and the "control interval" as 1 year before and 1 year after the risk interval. The incidence rate ratio (IRR) and 95% confidence interval (CI) for MACE were estimated by conditional Poisson regression. Finally, the primary outcome of the incidence of MACEs within one year of dengue was observed in 1,247 patients. The IRR of MACEs was 17.9 (95% CI 15.80-20.37) during the first week after the onset of DENV infection observed from 1,244 eligible patients. IRR were significantly higher for hemorrhagic stroke (10.9, 95% CI 6.80-17.49), ischemic stroke (15.56, 95% CI 12.44-19.47), AMI (13.53, 95% CI 10.13-18.06), and heart failure (27.24, 95% CI 22.67-32.73). No increased IRR was observed after day 14. CONCLUSIONS: The risks for MACEs are significantly higher in the immediate time period after dengue infection. Since dengue infection is potentially preventable by early recognition and vaccination, the dengue-associated MACE should be taken into consideration when making public health management policies.


Subject(s)
Dengue/complications , Heart Failure/complications , Myocardial Infarction/complications , Stroke/complications , Adolescent , Adult , Child , Child, Preschool , Dengue/epidemiology , Dengue Virus , Female , Heart Failure/epidemiology , Humans , Incidence , Infant , Male , Middle Aged , Myocardial Infarction/epidemiology , Risk Factors , Stroke/epidemiology , Taiwan/epidemiology
6.
Acta Trop ; 227: 106269, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1729465

ABSTRACT

Monte Verde, a peri­urban squatter community near San Pedro Sula, virtually eliminated Aedes aegypti production in all known larval habitats: wells; water storage containers including pilas (open concrete water tanks used for laundry), 200-liter drums, 1000-liter plastic "cisterns," buckets; and objects collecting rainwater. The project began in 2016 when Monte Verde was overrun with dengue, Zika, and chikungunya. During more than a year of experimentation, Monte Verde residents crafted an effective, sustainable, and environmentally friendly toolkit that was inexpensive but required full community participation. Biological control with copepods, turtles, and tilapia was at the core of the toolkit, along with a mix of other methods such as getting rid of unnecessary containers, scrubbing them to remove Ae. aegypti eggs, and covering them to exclude mosquitoes or rainwater. Environmentally friendly larvicides also had a limited but crucial role. Key design features: (1) toolkit components known to be nearly 100% effective at preventing Ae. aegypti production when fitted to appropriate larval habitats; (2) using Ae. aegypti larval habitats as a resource by transforming them into "egg sinks" to drive Ae. aegypti population decline; (3) dedicated community volunteers who worked with their neighbors, targeting 100% coverage of all known Ae. aegypti larval habitats with an appropriate control method; (4) monthly monitoring in which the volunteers visited every house to assess progress and improve coverage as an ongoing learning experience for both volunteers and residents. Taking pupae as an indicator of Ae. aegypti production, from September 2018 to the end of the record in December 2021 (except for a brief lapse during COVID lockdown in 2020), the monthly count of pupae fluctuated between zero and 0.6% of the 22,984 pupae counted in the baseline survey at the beginning of the project. Adult Ae. aegypti declined to low numbers but did not disappear completely. There were no recognizable cases of dengue, Zika, or chikungunya after June 2018, though the study design based on a single site did not provide a basis for rigorous confirmation that Monte Verde's Ae. aegypti control program was responsible. Nonetheless, Monte Verde's success at eliminating Ae. aegypti production can serve as a model for extending this approach to other communities. Key ingredients for success were outside stimulation and facilitation to foster shared community awareness and commitment regarding the problem and its solution, enduring commitment of local leadership, compatibility of the toolkit with the local community, overcoming social obstacles, rapid results with "success breeding success," and building resilience.


Subject(s)
Aedes , COVID-19 , Copepoda , Dengue , Tilapia , Turtles , Zika Virus Infection , Zika Virus , Aedes/physiology , Animals , Communicable Disease Control , Community Participation , Dengue/epidemiology , Dengue/prevention & control , Honduras , Humans , Larva , Mosquito Control/methods , SARS-CoV-2
7.
BMC Public Health ; 22(1): 388, 2022 02 24.
Article in English | MEDLINE | ID: covidwho-1700631

ABSTRACT

BACKGROUND: Dengue is the major mosquito-borne disease in Sri Lanka. After its first detection in January 2020, COVID-19 has become the major health issue in Sri Lanka. The impact of public health measures, notably restrictions on movement of people to curb COVID-19 transmission, on the incidence of dengue during the period March 2020 to April 2021 was investigated. METHODS: The incidence of dengue and COVID-19, rainfall and the public movement restrictions implemented to contain COVID-19 transmission were obtained from Sri Lanka government sources. A Seasonal Autoregressive Integrated Moving Average (SARIMA) model was used to predict the monthly dengue incidence from March 2020 to April 2021 for each of the country's 25 districts based on five years of pre-pandemic data, and compared with the actual recorded incidence of dengue during this period. Ovitrap collections of Aedes larvae were performed in Jaffna city in the Jaffna district from August 2020 to April 2021 and the findings compared with similar collections made in the pre-pandemic period from March 2019 to December 2019. RESULTS: The recorded numbers of dengue cases for every month from March 2020 to April 2021 in the whole country and for all 25 districts over the same period were lower than the numbers of dengue cases predicted from data for the five years (2015-2019) immediately preceding the COVID-19 pandemic. The number of dengue cases recorded nationwide represented a 74% reduction from the predicted number of dengue cases for the March 2020 to April 2021 period. The numbers of Aedes larvae collected from ovitraps per month were reduced by 88.6% with a lower proportion of Ae. aegypti than Ae. albopictus in Jaffna city from August 2020 until April 2021 compared with March 2019 to December 2019. CONCLUSION: Public health measures that restricted movement of people, closed schools, universities and offices to contain COVID-19 transmission unexpectedly led to a significant reduction in the reported numbers of dengue cases in Sri Lanka. This contrasts with findings reported from Singapore. The differences between the two tropical islands have significant implications for the epidemiology of dengue. Reduced access to blood meals and lower vector densities, particularly of Ae. aegypti, resulting from the restrictions on movement of people, are suggested to have contributed to the lower dengue incidence in Sri Lanka.


Subject(s)
Aedes , COVID-19 , Dengue , Animals , COVID-19/epidemiology , Dengue/epidemiology , Dengue/prevention & control , Humans , Incidence , Mosquito Vectors , Pandemics/prevention & control , SARS-CoV-2 , Sri Lanka/epidemiology
8.
Phys Life Rev ; 40: 65-92, 2022 03.
Article in English | MEDLINE | ID: covidwho-1683512

ABSTRACT

Mathematical models have a long history in epidemiological research, and as the COVID-19 pandemic progressed, research on mathematical modeling became imperative and very influential to understand the epidemiological dynamics of disease spreading. Mathematical models describing dengue fever epidemiological dynamics are found back from 1970. Dengue fever is a viral mosquito-borne infection caused by four antigenically related but distinct serotypes (DENV-1 to DENV-4). With 2.5 billion people at risk of acquiring the infection, it is a major international public health concern. Although most of the cases are asymptomatic or mild, the disease immunological response is complex, with severe disease linked to the antibody-dependent enhancement (ADE) - a disease augmentation phenomenon where pre-existing antibodies to previous dengue infection do not neutralize but rather enhance the new infection. Here, we present a 10-year systematic review on mathematical models for dengue fever epidemiology. Specifically, we review multi-strain frameworks describing host-to-host and vector-host transmission models and within-host models describing viral replication and the respective immune response. Following a detailed literature search in standard scientific databases, different mathematical models in terms of their scope, analytical approach and structural form, including model validation and parameter estimation using empirical data, are described and analyzed. Aiming to identify a consensus on infectious diseases modeling aspects that can contribute to public health authorities for disease control, we revise the current understanding of epidemiological and immunological factors influencing the transmission dynamics of dengue. This review provide insights on general features to be considered to model aspects of real-world public health problems, such as the current epidemiological scenario we are living in.


Subject(s)
COVID-19 , Dengue Virus , Dengue , Animals , Antibodies, Viral , Dengue/epidemiology , Humans , Models, Theoretical , Mosquito Vectors , Pandemics , SARS-CoV-2
10.
PLoS One ; 17(1): e0262473, 2022.
Article in English | MEDLINE | ID: covidwho-1627804

ABSTRACT

Several studies have reported the relationship of deforestation with increased incidence of infectious diseases, mainly due to the deregulation caused in these environments. The purpose of this study was to answer the following questions: a) is increased loss of vegetation related to dengue cases in the Brazilian Cerrado? b) how do different regions of the tropical savanna biome present distinct patterns for total dengue cases and vegetation loss? c) what is the projection of a future scenario of deforestation and an increased number of dengue cases in 2030? Thus, this study aimed to assess the relationship between loss of native vegetation in the Cerrado and dengue infection. In this paper, we quantify the entire deforested area and dengue infection cases from 2001 to 2019. For data analyses, we used Poisson generalized linear model, descriptive statistics, cluster analysis, non-parametric statistics, and autoregressive integrated moving average (ARIMA) models to predict loss of vegetation and fever dengue cases for the next decade. Cluster analysis revealed the formation of four clusters among the states. Our results showed significant increases in loss of native vegetation in all states, with the exception of Piauí. As for dengue cases, there were increases in the states of Minas Gerais, São Paulo, and Mato Grosso. Based on projections for 2030, Minas Gerais will register about 4,000 dengue cases per 100,000 inhabitants, São Paulo 750 dengue cases per 100,000 inhabitants, and Mato Grosso 500 dengue cases per 100,000 inhabitants. To reduce these projections, Brazil will need to control deforestation and implement public health, environmental and social policies, requiring a joint effort from all spheres of society.


Subject(s)
Conservation of Natural Resources/trends , Dengue/etiology , Brazil/epidemiology , Conservation of Natural Resources/statistics & numerical data , Dengue/epidemiology , Dengue Virus/pathogenicity , Ecosystem , Environment , Humans , Incidence
12.
Biochemistry ; 60(46): 3449-3451, 2021 11 23.
Article in English | MEDLINE | ID: covidwho-1590174

ABSTRACT

Single-particle cryogenic electron microscopy (cryo-EM), whose full power was not realized until the advent of powerful detectors in 2012, has a unique position as a method of structure determination as it is capable of providing information about not only the structure but also the dynamical features of biomolecules. This information is of special importance in understanding virus-host interaction and explains the crucial role of cryo-EM in the efforts to find vaccinations and cures for pandemics the world has experienced in the past decade.


Subject(s)
Cryoelectron Microscopy , Host Microbial Interactions , Single Molecule Imaging , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Coronavirus Infections/virology , Dengue/epidemiology , Dengue/prevention & control , Dengue/virology , Hemorrhagic Fever, Ebola/epidemiology , Hemorrhagic Fever, Ebola/prevention & control , Hemorrhagic Fever, Ebola/virology , Humans , Pandemics/prevention & control , Viral Vaccines/administration & dosage , Zika Virus Infection/epidemiology , Zika Virus Infection/prevention & control , Zika Virus Infection/virology
14.
Emerg Microbes Infect ; 11(1): 240-249, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-1585242

ABSTRACT

ABSTRACTThe COVID-19 pandemic and measures against it provided a unique opportunity to understand the transmission of other infectious diseases and to evaluate the efficacy of COVID-19 prevention measures on them. Here we show a dengue epidemic in Yunnan, China, during the pandemic of COVID-19 was dramatically reduced compared to non-pandemic years and, importantly, spread was confined to only one city, Ruili. Three key features characterized this dengue outbreak: (i) the urban-to-suburban spread was efficiently blocked; (ii) the scale of epidemic in urban region was less affected; (iii) co-circulation of multiple strains was attenuated. These results suggested that countermeasures taken during COVID-19 pandemic are efficient to prevent dengue transmission between cities and from urban to suburban, as well to reduce the co-circulation of multiple serotypes or genotypes. Nevertheless, as revealed by the spatial analysis, once the dengue outbreak was established, its distribution was very stable and resistant to measures against COVID-19, implying the possibility to develop a precise prediction method.


Subject(s)
Communicable Disease Control/methods , Dengue Virus , Dengue/epidemiology , Dengue/prevention & control , Dengue/transmission , Animals , COVID-19/epidemiology , COVID-19/prevention & control , China/epidemiology , Chlorocebus aethiops , Disease Outbreaks/prevention & control , Genotype , Humans , Pandemics/prevention & control , Phylogeny , RNA, Viral , SARS-CoV-2 , Serogroup , Spatial Analysis , Vero Cells
16.
Travel Med Infect Dis ; 45: 102232, 2022.
Article in English | MEDLINE | ID: covidwho-1569097

ABSTRACT

OBJECTIVES: The purpose of this cohort study was to develop two scores able to differentiate coronavirus 2019 (COVID-19) from dengue and other febrile illnesses (OFIs). METHODS: All subjects suspected of COVID-19 who attended the SARS-CoV-2 testing center of Saint-Pierre hospital, Reunion, between March 23 and May 10, 2020, were assessed for identifying predictors of both infectious diseases from a multinomial logistic regression model. Two scores were developed after weighting the odd ratios then validated by bootstrapping. RESULTS: Over 49 days, 80 COVID-19, 60 non-severe dengue and 872 OFIs were diagnosed. The translation of the best fit model yielded two scores composed of 11 criteria: contact with a COVID-19 positive case (+3 points for COVID-19; 0 point for dengue), return from travel abroad within 15 days (+3/-1), previous individual episode of dengue (+1/+3), active smoking (-3/0), body ache (0/+5), cough (0/-2), upper respiratory tract infection symptoms (-1/-1), anosmia (+7/-1), headache (0/+5), retro-orbital pain (-1/+5), and delayed presentation (>3 days) to hospital (+1/0). The area under the receiver operating characteristic curve was 0.79 (95%CI 0.76-0.82) for COVID-19 score and 0.88 (95%CI 0.85-0.90) for dengue score. Calibration was satisfactory for COVID-19 score and excellent for dengue score. For predicting COVID-19, sensitivity was 97% at the 0-point cut-off and specificity 99% at the 10-point cut-off. For predicting dengue, sensitivity was 97% at the 3-point cut-off and specificity 98% at the 11-point cut-off. CONCLUSIONS: COVIDENGUE scores proved discriminant to differentiate COVID-19 and dengue from OFIs in the context of SARS-CoV-2 testing center during a co-epidemic.


Subject(s)
COVID-19 , Dengue , Epidemics , COVID-19 Testing , Cohort Studies , Dengue/diagnosis , Dengue/epidemiology , Humans , SARS-CoV-2
17.
Clin Infect Dis ; 73(11): 2045-2054, 2021 12 06.
Article in English | MEDLINE | ID: covidwho-1560351

ABSTRACT

BACKGROUND: Immunity after dengue virus (DENV) infection has been suggested to cross-protect from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and mortality. METHODS: We tested whether serologically proven prior DENV infection diagnosed in September-October 2019, before the coronavirus disease 2019 (COVID-19) pandemic, reduced the risk of SARS-CoV-2 infection and clinically apparent COVID-19 over the next 13 months in a population-based cohort in Amazonian Brazil. Mixed-effects multiple logistic regression analysis was used to identify predictors of infection and disease, adjusting for potential individual and household-level confounders. Virus genomes from 14 local SARS-CoV-2 isolates were obtained using whole-genome sequencing. RESULTS: Anti-DENV immunoglobulin G (IgG) was found in 37.0% of 1285 cohort participants (95% confidence interval [CI]: 34.3% to 39.7%) in 2019, with 10.4 (95% CI: 6.7-15.5) seroconversion events per 100 person-years during the follow-up. In 2020, 35.2% of the participants (95% CI: 32.6% to 37.8%) had anti-SARS-CoV-2 IgG and 57.1% of the 448 SARS-CoV-2 seropositives (95% CI: 52.4% to 61.8%) reported clinical manifestations at the time of infection. Participants aged >60 years were twice more likely to have symptomatic COVID-19 than children under 5 years. Locally circulating SARS-CoV-2 isolates were assigned to the B.1.1.33 lineage. Contrary to the cross-protection hypothesis, prior DENV infection was associated with twice the risk of clinically apparent COVID-19 upon SARS-CoV-2 infection, with P values between .025 and .039 after adjustment for identified confounders. CONCLUSIONS: Higher risk of clinically apparent COVID-19 among individuals with prior dengue has important public health implications for communities sequentially exposed to DENV and SARS-CoV-2 epidemics.


Subject(s)
COVID-19 , Dengue , Brazil/epidemiology , Child , Child, Preschool , Cohort Studies , Dengue/epidemiology , Humans , Pandemics , SARS-CoV-2
18.
J Travel Med ; 28(8)2021 Dec 29.
Article in English | MEDLINE | ID: covidwho-1546002
19.
J Med Virol ; 94(1): 366-371, 2022 01.
Article in English | MEDLINE | ID: covidwho-1544350

ABSTRACT

Co-epidemics happening simultaneously can generate a burden on healthcare systems. The co-occurrence of SARS-CoV-2 with vector-borne diseases (VBD), such as malaria and dengue in resource-limited settings represents an additional challenge to the healthcare systems. Herein, we assessed the coinfection rate between SARS-CoV-2 and VBD to highlight the need to carry out an accurate diagnosis and promote timely measures for these infections in Luanda, the capital city of Angola. This was a cross-sectional study conducted with 105 subjects tested for the SARS-CoV-2 and VBD with a rapid detection test in April 2021. The participants tested positive for SARS-CoV-2 (3.80%), malaria (13.3%), and dengue (27.6%). Low odds related to testing positivity to SARS-CoV-2 or VBD were observed in participants above or equal to 40 years (odds ratio [OR]: 0.60, p = 0.536), while higher odds were observed in male (OR: 1.44, p = 0.392) and urbanized areas (OR: 3.78, p = 0.223). The overall co-infection rate between SARS-CoV-2 and VBD was 11.4%. Our findings showed a coinfection between SARS-CoV-2 with malaria and dengue, which could indicate the need to integrate the screening for VBD in the SARS-CoV-2 testing algorithm and the adjustment of treatment protocols. Further studies are warranted to better elucidate the relationship between COVID-19 and VBD in Angola.


Subject(s)
COVID-19/epidemiology , Coinfection/epidemiology , Dengue/epidemiology , Malaria/epidemiology , Vector Borne Diseases/epidemiology , Adolescent , Adult , Age Factors , Angola/epidemiology , Antibodies, Protozoan/blood , Antibodies, Viral/blood , COVID-19 Testing , Chikungunya Fever/epidemiology , Child , Child, Preschool , Cross-Sectional Studies , Female , Humans , Infant , Infant, Newborn , Male , Mass Screening , Middle Aged , RNA, Viral/blood , SARS-CoV-2/isolation & purification , Sex Factors , Young Adult , Zika Virus Infection/epidemiology
20.
Int J Environ Res Public Health ; 18(22)2021 11 16.
Article in English | MEDLINE | ID: covidwho-1534046

ABSTRACT

The spatial-temporal assessment of vector diseases is imperative to design effective action plans and establish preventive strategies. Therefore, such assessments have potential public health planning-related implications. In this context, we here propose an integrated spatial disease evaluation (I-SpaDE) framework. The I-SpaDE integrates various techniques such as the Kernel Density Estimation, the Optimized Hot Spot Analysis, space-time assessment and prediction, and the Geographically Weighted Regression (GWR). It makes it possible to systematically assess the disease concentrations, patterns/trends, clustering, prediction dynamics, and spatially varying relationships between disease and different associated factors. To demonstrate the applicability and effectiveness of the I-SpaDE, we apply it in the second largest city of Pakistan, namely Lahore, using Dengue Fever (DF) during 2007-2016 as an example vector disease. The most significant clustering is evident during the years 2007-2008, 2010-2011, 2013, and 2016. Mostly, the clusters are found within the city's central functional area. The prediction analysis shows an inclination of DF distribution from less to more urbanized areas. The results from the GWR show that among various socio-ecological factors, the temperature is the most significantly associated with the DF followed by vegetation and built-up area. While the results are important to understand the DF situation in the study area and have useful implications for public health planning, the proposed framework is flexible, replicable, and robust to be utilized in other similar regions, particularly in developing countries in the tropics and sub-tropics.


Subject(s)
Dengue , Dengue/epidemiology , Humans , Pakistan/epidemiology , Risk Factors , Spatial Regression , Spatio-Temporal Analysis
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