Appropriate models for the management of infectious diseases

Background Mathematical models have become invaluable management tools for epidemiologists, both shedding light on the mechanisms underlying observed dynamics as well as making quantitative predictions on the effectiveness of different control measures. Here, we explain how substantial biases are introduced by two important, yet largely ignored, assumptions at the core of the vast majority of such models. Methods and Findings First, we use analytical methods to show that (i) ignoring the latent period or (ii) making the common assumption of exponentially distributed latent and infectious periods (when including the latent period) always results in underestimating the basic reproductive ratio of an infection from outbreak data. We then proceed to illustrate these points by fitting epidemic models to data from an influenza outbreak. Finally, we document how such unrealistic a priori assumptions concerning model structure give rise to systematically overoptimistic predictions on the outcome of potential management options. Conclusion This work aims to highlight that, when developing models for public health use, we need to pay careful attention to the intrinsic assumptions embedded within classical frameworks

Biology of Diachasmimorpha longicaudata, A Parasitoid of Carambola Fruit Fly, (Diptera; Tephritidae)

The life cycle study of Diachasmimorpha longicaudata, a larval parasitoid of Bactrocera (B) sp. near Bactrocera dorsalis A, was conducted in the laboratory (26°C± 1.5°). There were 4 larval stages based on the size of the mouthhook. The first larval moult occurred in the newly formed pupanum of the host. The entire developmental periods for males and females were 16.3 ± 0.8 day and 17.5 ± 0.8 days, respectively. The average reproductive capacity per female during the life-span was 92 ± 4.5 eggs

The Life-cycle of biosteres persulcatus with reference to adults' reproductive capacity on eggs of Carambola fruit-fly

A study of the life-cycle of Biosteres persulcatus Silvestri, a larval parasitoid of (Bactrocera (B) sp. near Bactrocera dorsalis A), was conducted in the laboratory (26.50C± 1.50 C). There are 4 larval stages as indicated by the sizes of the mouthhooks. The first larval moult occurred in the newly{ormed puparium of the host. The entire developmental period from egg to adult emergence for male and female was 16.3± 0.80 days and 1 7.1 ± 0.80 days respectively. The average reproductive capacity during the life span was 67 ± 3.5 eggs

Pengukuran Efektivitas Kulit Singkong, Kulit Ubi Jalar, Kulit Pisang Dan Kulit Jeruk Sebagai Bahan Penyerap Besi (Fe) Dan Mangan (Mn) Pada Air Lindi Tpa

Air lindi merupakan cairan yang berasal dari timbunan sampah dengan kandungan unsur-unsur berbahaya seperti logam besi (Fe) dan mangan (Mn).Beberapa bahan terbuang yang memiliki kemampuan untuk menyerap logam dengan harga terjangkau, aman dan memiliki daya serap yang tinggi yaitu kulit singkong, kulit ubi jalar, kulit pisang dan kulit jeruk.Penelitian ini bertujuan untuk mengukur efektivitas keempat adsorben tersebut dalam mengadsorpsi logam besi (Fe) dan mangan (Mn) pada air lindi. Proses penelitian pendahuluan dilakukan dengan menginteraksikan masing-masing adsorben dengan limbah buatan untuk logam Fe dan Mn dengan konsentrasi 15 ppm dalam waktu 15, 30, 45, 60 dan 75 menit. Pengukuran efektivitas penyerapan masing-masing adsorben terhadap masing-masing logam pada limbah buatan dapat diketahui berdasarkan besarnya persentase penyerapan dan lamanya waktu yang dibutuhkan hingga mencapai kesetimbangan.Hasil berupa waktu optimum penyerapan adsorben yang diperoleh dari adsorpsi logam pada limbah buatan ini kemudian diaplikasikan pada air lindi. Hasil interaksi antara adsorben dengan logam pada air lindi selama waktu optimum menunjukkan bahwa efektifitas tertinggi untuk penyerapan logam Fe yaitu sebesar 56.54% oleh kulit singkong, untuk logam Mn yaitu sebesar 14.41% oleh kulit pisang

Prohilila (Produksi Hidrogen Dari Limbah Laboratorium) Sebagai Mediator Energi Pembangkit Listrik Dengan Metode Fuel Cell

Laboratorium merupakan sarana dalam pengembangan ilmu pengetahuan khususnya dalam bidang keilmuan dalam menunjang keberhasilan penemuan hal-hal baru melalui penelitian. Mengingat banyaknya jenis limbah lab FMIPA UII yang berbahaya, termasuk juga limbah cair dari laboratorium yang bersifat toksik yang memiliki unsur logam berat sehingga mencemari lingkungan serta bepengaruh pada kesehatan manusia. Maka diperlukan upaya untuk pengatasan serta memberikan inovasi baru dari limbah cair kimia. Salah satunya dilakukan pengelolaan menggunakan teknik fuel cell yang merupakan energi masa depan yaitu sistem elektrokimia yang dapat mengubah energi kimia dari hidrogen dan oksigen yang langsung menjadi energi listrik. Keuntungannya pembakaran lebih konvensional yang berbasis teknologi dan tidak memancarkan emisi pada saat operasi, merupakan green house gases mengatasi polusi udara. Pemanfaatan limbah laboratorium dengan metode fuel cel ini bertujuan agar pencemaran lingkungan oleh zat kimia dapat diminimalkan dan dapat mengubahnya menjadi daya energi listrik. Untuk mendukung gagasan ini, maka perlu dilakukannya studi lebih lanjut mengenai proses pemanfaatan limbah menjadi energi listrik menggunakan metode fuel cell. Dimana dengan menggunakan fuel cell, satu kg H2 dapat menghasilkan 33,9 kWh energi listrik atau sama dengan 33.900 watt per jam. Prediksi hasil dari pemanfaatan limbah ini yaitu terbentuknya kemandirian untuk memenuhi kebutuhan listrik terutama di laboratorium hingga dapat memberikan solusi untuk menghasilkan energi yang terbarukan

Classifying the unknown: discovering novel gravitational-wave detector glitches using similarity learning

The observation of gravitational waves from compact binary coalescences by LIGO and Virgo has begun a new era in astronomy. A critical challenge in making detections is determining whether loud transient features in the data are caused by gravitational waves or by instrumental or environmental sources. The citizen-science project \emph{Gravity Spy} has been demonstrated as an efficient infrastructure for classifying known types of noise transients (glitches) through a combination of data analysis performed by both citizen volunteers and machine learning. We present the next iteration of this project, using similarity indices to empower citizen scientists to create large data sets of unknown transients, which can then be used to facilitate supervised machine-learning characterization. This new evolution aims to alleviate a persistent challenge that plagues both citizen-science and instrumental detector work: the ability to build large samples of relatively rare events. Using two families of transient noise that appeared unexpectedly during LIGO's second observing run (O2), we demonstrate the impact that the similarity indices could have had on finding these new glitch types in the Gravity Spy program

The Link between Dengue Incidence and El Niño Southern Oscillation

Pejman Rohani discusses a new study that examined the dynamic relationship between climate variables and dengue incidence in Thailand, Mexico, and Puerto Rico

Immune Boosting Explains Regime-Shifts in Prevaccine-Era Pertussis Dynamics

Understanding the biological mechanisms underlying episodic outbreaks of infectious diseases is one of mathematical epidemiology’s major goals. Historic records are an invaluable source of information in this enterprise. Pertussis (whooping cough) is a re-emerging infection whose intermittent bouts of large multiannual epidemics interspersed between periods of smaller-amplitude cycles remain an enigma. It has been suggested that recent increases in pertussis incidence and shifts in the age-distribution of cases may be due to diminished natural immune boosting. Here we show that a model that incorporates this mechanism can account for a unique set of pre-vaccine-era data from Copenhagen. Under this model, immune boosting induces transient bursts of large amplitude outbreaks. In the face of mass vaccination, the boosting model predicts larger and more frequent outbreaks than do models with permanent or passively-waning immunity. Our results emphasize the importance of understanding the mechanisms responsible for maintaining immune memory fo