Analisis Perbandingan Bilangan Reproduksi Dasar pada Model Penyebaran Penyakit Dengue dengan Pengaruh Faktor Usia di Kota Bandung

Penyakit Dengue merupakan salah satu masalah kesehatan yang utama di masyarakat Indonesia pada umumnya dan di kota Bandung pada khususnya. Pada penyebarannya, ternyata terdapat perbedaan tingkat risiko transmisi antara kelompok usia anak dan orang dewasa pada penyakit Dengue. Sebagai salah satu strategi pencegahan penyebaran penyakit ini, dapat dengan melalui pemodelan dari sistem dinamika penyebarannya. Penelitian ini akan menganalisa model penyebaran penyakit Dengue di kota Bandung dengan memperhitungkan faktor individu anak dengan kasus simtomatik dan asimtomatik. Bilangan Reproduksi Dasar (BRD) sebagai nilai ambang batas penyebaran penyakit ini akan dicari dan dianalisis dengan menggunakan metode Matriks Generasi dan Laju Pertumbuhan Intrinsik dan dengan menerapkan nilai parameter-parameter dan data banyaknya kasus dengue di kota Bandung pada tahun 2016-2018. Titik kesetimbangan dari kondisi bebas penyakit dan endemik juga  akan ditentukan untuk memverifikasi keakuratan model yang dibuat. Dari hasil analisisnya, disimpulkan bahwa kedua metode menghasilkan bentuk BRD yang memiliki karakter yang berbeda dan diterapkan pada kondisi yang berbeda pula. Jika data real tersedia, maka lebih baik menerapkan metode Laju Pertumbuhan Intrinsik. Sebaliknya, jika data real tidak lengkap tersedia, maka disarankan menggunakan metode Matriks Generas

A systematic review of the data, methods and environmental covariates used to map Aedes-borne arbovirus transmission risk

BACKGROUND: Aedes (Stegomyia)-borne diseases are an expanding global threat, but gaps in surveillance make comprehensive and comparable risk assessments challenging. Geostatistical models combine data from multiple locations and use links with environmental and socioeconomic factors to make predictive risk maps. Here we systematically review past approaches to map risk for different Aedes-borne arboviruses from local to global scales, identifying differences and similarities in the data types, covariates, and modelling approaches used. METHODS: We searched on-line databases for predictive risk mapping studies for dengue, Zika, chikungunya, and yellow fever with no geographical or date restrictions. We included studies that needed to parameterise or fit their model to real-world epidemiological data and make predictions to new spatial locations of some measure of population-level risk of viral transmission (e.g. incidence, occurrence, suitability, etc.). RESULTS: We found a growing number of arbovirus risk mapping studies across all endemic regions and arboviral diseases, with a total of 176 papers published 2002-2022 with the largest increases shortly following major epidemics. Three dominant use cases emerged: (i) global maps to identify limits of transmission, estimate burden and assess impacts of future global change, (ii) regional models used to predict the spread of major epidemics between countries and (iii) national and sub-national models that use local datasets to better understand transmission dynamics to improve outbreak detection and response. Temperature and rainfall were the most popular choice of covariates (included in 50% and 40% of studies respectively) but variables such as human mobility are increasingly being included. Surprisingly, few studies (22%, 31/144) robustly tested combinations of covariates from different domains (e.g. climatic, sociodemographic, ecological, etc.) and only 49% of studies assessed predictive performance via out-of-sample validation procedures. CONCLUSIONS: Here we show that approaches to map risk for different arboviruses have diversified in response to changing use cases, epidemiology and data availability. We identify key differences in mapping approaches between different arboviral diseases, discuss future research needs and outline specific recommendations for future arbovirus mapping

Spatial connectivity in mosquito-borne disease models: a systematic review of methods and assumptions

This is the final version. Available from The Royal Society via the DOI in this record.Data extracted from the studies included in this systematic review are available from https://github.com/sophie-a-lee/mbd_connectivity_review and archived in a permanent repository on Zenodo (http://doi.org/10.5281/zenodo.4706866).Spatial connectivity plays an important role in mosquito-borne disease transmission. Connectivity can arise for many reasons, including shared environments, vector ecology and human movement. This systematic review synthesizes the spatial methods used to model mosquito-borne diseases, their spatial connectivity assumptions and the data used to inform spatial model components. We identified 248 papers eligible for inclusion. Most used statistical models (84.2%), although mechanistic are increasingly used. We identified 17 spatial models which used one of four methods (spatial covariates, local regression, random effects/fields and movement matrices). Over 80% of studies assumed that connectivity was distance-based despite this approach ignoring distant connections and potentially oversimplifying the process of transmission. Studies were more likely to assume connectivity was driven by human movement if the disease was transmitted by an Aedes mosquito. Connectivity arising from human movement was more commonly assumed in studies using a mechanistic model, likely influenced by a lack of statistical models able to account for these connections. Although models have been increasing in complexity, it is important to select the most appropriate, parsimonious model available based on the research question, disease transmission process, the spatial scale and availability of data, and the way spatial connectivity is assumed to occur.Engineering and Physical Sciences Research Council (EPSRC)The Royal Societ

Life Skills Education for Children with Special Needs In Order to Facilitate Vocational Skills

Children with special needs generally consist of children who experience delays and disruptions in their development so that require special handling to improve the ability of children with special needs. After conducting a survey at several extraordinary schools (SLB) in Makassar, it was found that the conventional delivery of materials from teachers resulted in an uncomfortable situation so that the students 'interest to learn a particular subject was very low, therefore a learning method was needed that could attract students' interest in following the lesson. Students hope to gain more knowledge and experience as study results, while teachers, on the other hand, expect that practical learning process can bring achievement in term of better cognitive, psychomotor, affective changes, and improvement of student life skill. After producing a Multimedia Based Learning model, this research carried out trial test on the developed product to several students of SLB (Sekolah Luar Biasa) in Makassar. It was found that the use of this Multimedia Based Learning Model by SLB students can develop their life skills such as personal skills, thinking skills, social skills, and vocational skills

Climate change and childhood diarrhoea in Kathmandu, Nepal: a health risk assessment and exploration of surveillance capacity

There is substantial evidence that the onset and transmission of infectious diseases, particularly vector-borne diseases and diarrheal diseases, are influenced by many factors including climate change. Improving the understanding of the impacts of climate change on infectious diseases is important to inform policy decision making on disease control and prevention, as well as predicting the trends in the infectious diseases burden. Epidemiological analysis of long-term surveillance data on infectious diseases and meteorological factors are instrumental in establishing the association between infectious disease incidence and climate change. Advanced epidemiological techniques are now available to precisely estimate the nature of association (linear, non-linear) as well as the delayed effect: this means that it is possible to plan and design climate-based early warning systems to predict conditions that are likely to be favourable for an outbreak of climate-sensitive infectious disease. However, the association between infectious diseases and climate change varies, depending upon the pathogens responsible for infection. Similarly, the ability of infectious disease surveillance systems or disease control divisions to generate this evidence and utilise the knowledge to cope or adapt to the impacts of climate change is contingent upon the social, economic, political and other contextual problems. In the Nepalese context, the impacts of climate change on infectious diseases, in particular diarrheal disease, remains unknown: similarly, there has been no exploration of the contextual factors associated with the integration of climate change-related risk in Nepalese infectious diseases surveillance systems. Given this background, the first aim of this PhD thesis is to characterize the association between diarrhoea among children below five years of age and climate variables in Kathmandu, Nepal and then project the future burden of diarrhoea due to climate change. The second aim is to understand the association between rotavirus infection among children below five years of age and temperature variability in Kathmandu and compute the fraction of rotavirus infection that is attributable to temperature. The third aim is to explore the extant research on climate change and infectious diseases in Nepal and to identify the reasons behind sparse evidence on the topic. The final aim is to explore social, economic and cultural factors associated with infectious diseases surveillance in Nepal in the context of climate change. A mixed method study design was employed to achieve the goals of this project. There are four analytical chapters in this thesis: two quantitative studies; a study that reviews evidence of the impacts of climate change on infectious disease and policy documents related to infectious disease control and prevention in Nepal; and a qualitative study. Two quantitative studies were carried out to estimate the association between climate variability and childhood diarrhoea, and childhood rotavirus infection in Kathmandu. Study 1 and study 2 utilised time series design involving Poisson regression equations fitted with distributed lag models to characterise exposure-response and possible lagged association between climate variables and diarrhoea, and rotavirus infection. A qualitative research study was undertaken to explore the social, economic, cultural and political factors associated with infectious diseases surveillance in the context of climate change in Nepal. In study 4, semi-structured interviews were conducted with key informants and stakeholders from the Department of Health Services Nepal, World Health Organization Nepal, the Department of Hydrology and Meteorology Nepal and infectious disease experts working in both public and private sectors in Nepal. The interviews and subsequent thematic analysis of data were conducted from a critical realist perspective. Study 1 established a significant positive association between childhood diarrhoea and temperature, and rainfall. A 1°C increase in maximum temperature above the monthly average was found to be associated with 8.1% (RR: 1.081; 95% CI: 1.02-1.14) increase in the monthly count of diarrhoea among children below five years of age living in Kathmandu, Nepal. Similarly, a 10mm increase in monthly cumulative rainfall above the mean value was associated with 0.09% (RR: 1.009; 95% CI: 1.004-1.015) increase in childhood diarrhoea. It was further projected that 1357 (UI: 410–2274) additional cases of childhood diarrhoea could be experienced by 2050 given the projected change in climate under low-risk scenario (0.9°C increase in maximum temperature). Study 2 established a nonlinear negative association between temperature (maximum, mean and minimum) and weekly rotavirus infection cases among children below five years of age in Kathmandu. Compared to the median value of mean temperature, an increased risk (RR: 1.52; 95% CI: 1.08–2.15) of rotavirus infection was detected at the lower quantile (10th percentile) and a decreased risk (RR: 0.64; 95% CI: 0.43–0.95) was detected at the higher quantile (75th percentile). Similarly, an increased risk [(RR: 1.93; 95% CI: 1.40–2.65) and (RR: 1.42; 95% CI: 1.04–1.95)] of infection was detected for both maximum and minimum temperature at their lower quantile (10th percentile). It was further estimated that 47.01% of the rotavirus infection cases reported between 2013 and 2016 in Kathmandu could be attributed to minimum temperature. Study 3 identified that there was little evidence describing the impacts of climate change on infectious diseases and no evidence describing the projected burden under climate change scenarios. I explored the reasons behind paucity in the evidence and challenges faced by epidemiologists in Nepal. The challenges identified included poor quality infectious disease datasets, shortage of trained human resources, inadequate funding and political instability. As such, it was recommended that an integrated digital network of interdisciplinary experts be established and increased collaboration among different stakeholders be promoted to advance the evidence base on the impacts of climate change on infectious diseases in Nepal. The fourth and final study outlined that climate change and its impacts on infectious disease surveillance is treated as a less serious issue than other more ‘salient’ public health risks in the context of Nepal. The study further illustrates how climate change is variably constructed as a contingent risk for infectious diseases transmission and public health systems. The analysis exposes a weaker alliance among different stakeholders, particularly policymakers and evidence generators that leads to the continuation of traditional practices of infectious diseases surveillance without consideration of the impacts of climate change. In summary, this thesis brings to prominence important progress in understanding the link between climate change and infectious diseases, in particular childhood diarrhoea, in a subtropical highland climate from a low and middle income South Asian country. So far, we have not found any other study that explores the contextual factors (social, economic, cultural and political) that impede the integration of climate change-related risk in the disease surveillance systems. Therefore, this thesis illustrates a novel facet of infectious disease surveillance and climate change. This thesis makes an important contribution to address the gap on information related to climate change and infectious diseases in Nepal and can have significant implications towards building a climate-resilient public health system in Nepal.Thesis (Ph.D.) -- University of Adelaide, School of Public Health, 202

Ultrasensitive detection of toxocara canis excretory-secretory antigens by a nanobody electrochemical magnetosensor assay.

peer reviewedHuman Toxocariasis (HT) is a zoonotic disease caused by the migration of the larval stage of the roundworm Toxocara canis in the human host. Despite of being the most cosmopolitan helminthiasis worldwide, its diagnosis is elusive. Currently, the detection of specific immunoglobulins IgG against the Toxocara Excretory-Secretory Antigens (TES), combined with clinical and epidemiological criteria is the only strategy to diagnose HT. Cross-reactivity with other parasites and the inability to distinguish between past and active infections are the main limitations of this approach. Here, we present a sensitive and specific novel strategy to detect and quantify TES, aiming to identify active cases of HT. High specificity is achieved by making use of nanobodies (Nbs), recombinant single variable domain antibodies obtained from camelids, that due to their small molecular size (15kDa) can recognize hidden epitopes not accessible to conventional antibodies. High sensitivity is attained by the design of an electrochemical magnetosensor with an amperometric readout with all components of the assay mixed in one single step. Through this strategy, 10-fold higher sensitivity than a conventional sandwich ELISA was achieved. The assay reached a limit of detection of 2 and15 pg/ml in PBST20 0.05% or serum, spiked with TES, respectively. These limits of detection are sufficient to detect clinically relevant toxocaral infections. Furthermore, our nanobodies showed no cross-reactivity with antigens from Ascaris lumbricoides or Ascaris suum. This is to our knowledge, the most sensitive method to detect and quantify TES so far, and has great potential to significantly improve diagnosis of HT. Moreover, the characteristics of our electrochemical assay are promising for the development of point of care diagnostic systems using nanobodies as a versatile and innovative alternative to antibodies. The next step will be the validation of the assay in clinical and epidemiological contexts