High Spikes Research Articles

Application of three methods in water‐saving wheat breeding

AbstractAt present, water shortage seriously affects wheat production in many parts of the world, and to solve this problem, water‐saving wheat breeding is an important research domain. The objective of this study was to evaluate water‐saving index (WSI), yield factors, and KASP (kompetitive allele specific polymerase chain reaction) markers in water‐saving wheat breeding carried out in Hengshui region, China. The result showed as follows: (1) The new index WSI could better indicate the water‐saving performance, including the yield potential and the stability of different wheat cultivars under water limited condition (WL). (2) Referring to the degree of heat stress (D) in that year, selecting one of the three yield factors as the focus will improve the breeding efficiency of water‐saving wheat cultivars. With the increase of the D within a certain range, high water‐saving wheat cultivars showed a high grain weight (GW) under WL. Meanwhile with the decreasing of D value, high water‐saving wheat cultivars showed high spike number under WL. (3) KASP aggregation breeding will significantly improve the efficiency of water‐saving breeding. The combination with the highest effective rate of selecting water‐saving varieties carried GS5‐2334‐SNP and Dreb_SNP favorable alleles, and GW2‐6B‐1709SNP, TaMoc‐2433, and 1fehw with adverse alleles, whereas GS5‐2334‐SNP and GW2‐6B‐1709SNP that related to GW were useful markers for water‐saving breeding. These results improved our knowledge on the usage of WSI, yield factors, and KASP markers on water‐saving wheat breeding.

Multi-Residue Screening of Pesticides in Aquatic Products Using High-Performance Liquid Chromatography-Tandem High-Resolution Mass Spectrometry

Pesticide residues in aquatic products are of great concern due to the risk of environmental transmission and their extensive use in aquaculture. In our work, a quick screening approach was developed for the qualitative and semi-quantitative screening of 87 pesticide residues in aquatic products. The sample preparation was investigated, including extract solvent, extract methods, buffer salts, lipid removal, cleanup materials and filter membranes for aquatic products. Samples were extracted using a modified QuEChERS procedure, and two clean-up procedures were developed for UHPLC-Q/Orbitrap MS analysis based on the fat content of the aquatic products. The screening detection limits for all studied pesticides were distributed between 1 and 500 μg/kg in the three representative matrices. Seventy-one pesticides could be analyzed with a screening limit between 1 and 25 μg/kg in grass carp and crayfish, sixty-one pesticides could be screened for limits between 1 and 50 μg/kg in crab. The accuracy results showed that recoveries ranged from 50 to 120% for 60, 56 and 52 pesticides at medium-level for grass carp, crayfish and crab, respectively. At high spiking levels, 74, 65 and 59 pesticides were recovered within the range of 50-120% for the three matrices, respectively. The relative standard deviations of most compounds in different matrices were less than 20%. With this method, the local farmed aquatic products were tested for pesticide residues. In these samples, ethoxyquinoline, prometryn and phoxim were frequently detected. The majority of these confirmed compounds did not exceed 2.00 μg/kg. A grass carp with trichlorfon at 4.87 μg/kg and two carps with ethoxyquinoline at 200 µg/kg were detected, indicating the potential dietary risk.

Hydrofluoric Acid-Free Digestion of Organosilicon Nanoparticles for Bioanalysis by ICP-OES

A novel ICP-OES method has been developed for the determination of Si concentration, originating from polyorganophosphosilanes, in biological specimens that also contain metal ions. The method is free of hazardous hydrofluoric acid (HF) and involves digestion with HNO3/H2O2 prior to the analysis by ICP-OES. High and reproducible spike recovery was obtained from the controls.

Quantifying trial-by-trial variability during cortico-cortical evoked potential mapping of epileptogenic tissue.

Measuring cortico-cortical evoked potentials (CCEPs) is a promising tool for mapping epileptic networks, but it is not known how variability in brain state and stimulation technique might impact the use of CCEPs for epilepsy localization. We test the hypotheses that (1) CCEPs demonstrate systematic variability across trials and (2) CCEP amplitudes depend on the timing of stimulation with respect to endogenous, low-frequency oscillations. We studied 11 patients who underwent CCEP mapping after stereo-electroencephalography electrode implantation for surgical evaluation of drug-resistant epilepsy. Evoked potentials were measured from all electrodes after each pulse of a 30 s, 1Hz bipolar stimulation train. We quantified monotonic trends, phase dependence, and standard deviation (SD) of N1 (15-50 ms post-stimulation) and N2 (50-300 ms post-stimulation) amplitudes across the 30 stimulation trials for each patient. We used linear regression to quantify the relationship between measures of CCEP variability and the clinical seizure-onset zone (SOZ) or interictal spike rates. We found that N1 and N2 waveforms exhibited both positive and negative monotonic trends in amplitude across trials. SOZ electrodes and electrodes with high interictal spike rates had lower N1 and N2 amplitudes with higher SD across trials. Monotonic trends of N1 and N2 amplitude were more positive when stimulating from an area with higher interictal spike rate. We also found intermittent synchronization of trial-level N1 amplitude with low-frequency phase in the hippocampus, which did not localize the SOZ. These findings suggest that standard approaches for CCEP mapping, which involve computing a trial-averaged response over a .2-1Hz stimulation train, may be masking inter-trial variability that localizes to epileptogenic tissue. We also found that CCEP N1 amplitudes synchronize with ongoing low-frequency oscillations in the hippocampus. Further targeted experiments are needed to determine whether phase-locked stimulation could have a role in localizing epileptogenic tissue.

Electricity Load and Price Forecasting Using a Hybrid Method Based Bidirectional Long Short-Term Memory with Attention Mechanism Model

The accuracy of forecasting short- or medium-term electricity loads and prices is critical in the energy market. The amplitude and duration of abnormally high prices and load spikes can be detrimental to retailers and production systems. Therefore, predicting these spikes to effectively manage risk is critical. In this paper, a novel hybrid method that combines ensemble empirical mode decomposition (EEMD) algorithm and a bidirectional long short-term memory with attention mechanism (BiLSTM-AM) model is proposed to predict electricity loads and prices. A simple approach is proposed to determine the number of intrinsic mode functions (IMFs) that decompose raw data using EEMD to avoid overdecomposition, irrelevant components, and high computational cost. Each selected mode is then modeled with BiLSTM-AM to obtain a predicted sequence. These sequences are summed and then reverted to obtain the final predicted value. The proposed method is validated using two datasets (PMJ and Australian Energy Market Operator) with different time intervals to demonstrate the generality and robustness of the forecasts, especially in temporal valley or peak forecasting. The results show that the proposed method outperforms other methods in prediction accuracy and spike-capturing ability, with EEMD reducing the mean absolute percentage error (MAPE) by 53%, 54%, and 60%, respectively. In the three forecast periods, the average MAPE and R ̲ 2 are 0.097 and 0.92, respectively. Furthermore, we use Kolmogorov-Smirnov predictive accuracy (KSPA) test and model confidence set (MCS) test to validate the superiority of the proposed model. The results demonstrate its suitability, reliability, and performance in short- and medium-term forecasting.

Highly Reliable Push–Pull Resonant DC/DC Converter for Medium-Power Applications

This article presents a highly reliable push–pull resonant dc/dc converter for medium-power applications. At medium power, conventional push–pull resonant dc/dc converter experiences a very high current spike at the secondary-side switches, and this spike can destroy the active power components. We eliminate this current spike by connecting clamp diodes to the resonant capacitors. Moreover, the proposed converter achieves fully zero-voltage-switching (ZVS) turn- <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small> at the secondary-side switches when the load exceeds the threshold. Furthermore, the proposed converter is invulnerable to the short-circuit problem at the output. Experimental results are presented to show the effectiveness of the proposed dc/dc converter at the medium power against a conventional solution.

SpaRCe: Improved Learning of Reservoir Computing Systems Through Sparse Representations.

"Sparse" neural networks, in which relatively few neurons or connections are active, are common in both machine learning and neuroscience. While, in machine learning, "sparsity" is related to a penalty term that leads to some connecting weights becoming small or zero, in biological brains, sparsity is often created when high spiking thresholds prevent neuronal activity. Here, we introduce sparsity into a reservoir computing network via neuron-specific learnable thresholds of activity, allowing neurons with low thresholds to contribute to decision-making but suppressing information from neurons with high thresholds. This approach, which we term "SpaRCe," optimizes the sparsity level of the reservoir without affecting the reservoir dynamics. The read-out weights and the thresholds are learned by an online gradient rule that minimizes an error function on the outputs of the network. Threshold learning occurs by the balance of two opposing forces: reducing interneuronal correlations in the reservoir by deactivating redundant neurons, while increasing the activity of neurons participating in correct decisions. We test SpaRCe on classification problems and find that threshold learning improves performance compared to standard reservoir computing. SpaRCe alleviates the problem of catastrophic forgetting, a problem most evident in standard echo state networks (ESNs) and recurrent neural networks in general, due to increasing the number of task-specialized neurons that are included in the network decisions.

Learning Super-Resolution Reconstruction for High Temporal Resolution Spike Stream

Spike camera is a new type of bio-inspired vision sensor, each pixel of which perceives the brightness of the scene independently, and finally outputs 3-dimensional spatiotemporal spike streams. To bridge the spike camera and traditional frame-based vision, there is some works to reconstruct spike streams into regular images. However, the low spatial resolution ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$400\times 250$ </tex-math></inline-formula> ) of the spike camera limits the quality of the reconstructed images. Thus, it is meaningful to explore a super-resolution reconstruction for spike streams. In this paper, we propose an end-to-end network to reconstruct high-resolution images from low-resolution spike streams. To utilize more spatiotemporal features of spike streams, our network adopts a multi-level features learning mechanism, including intra-stream feature extraction by spike encoder, inter-stream dependencies extraction based on optical flow module, and joint features learning via spike-based iterative projection. Experimental results demonstrate that our network is superior to the combination of state-of-the-art intensity image reconstruction methods and super-resolution networks on simulated and real datasets.

A Family of High Step-Up Magnetically Coupled Impedance Source Inverters With Clamped DC-Link Voltage and Low Shoot-Through Current

The use of coupled inductors in impedance source inverters improves the voltage gain performance at the expense of high dc-link voltage spikes and shoot-through (ST) currents. The result is an increase in voltage and current stresses on semiconductors, as well as reactive element capacity and overall losses. Thus, to overcome these problems, this letter proposes a new family of magnetically coupled impedance source inverters with a smooth dc-link voltage, a low ST current, and a higher voltage gain that are confirmed through experimental tests.

Externally-Triggered Spiking and Spiking Cluster Oscillation in Broadband Optoelectronic Oscillator

An approach to generating periodic spiking and spiking cluster in a broadband nonlinear opto-electronic oscillator (OEO) is proposed and demonstrated. Through injecting a long-duration square-wave pulse train with a repetition frequency equal to an integral multiple of the free spectral range into the OEO with a high net gain, controllable spiking and spiking cluster oscillation can be achieved when the dual-drive Mach-Zehnder modulator (DDMZM) in the OEO is biased far away from its quadrature point. The proposed scheme is verified by both numerical simulation and experiment. The results indicate that, when the DDMZM in the OEO cavity is biased near its minimum transmission point, positive spiking train with nanosecond-level pulse width is excited by the rising edge of the injected square-wave pulse train. Through further enhancing the injection strength, uniformly-spaced positive spiking fills the high-level voltage duration of each injected square-wave pulse. Hence, spiking cluster oscillation is achieved. Benefiting from its controllability, this approach can be applied in ultra-wideband (UWB) communications, electronic countermeasures, spiking coding and high-speed neuromorphic computing.

A Coupled Inductor Based Ćuk Microinverter for Single Phase Grid Connected PV Applications

A single phase, single stage, non-isolated microinverter scheme is proposed in this paper which can address the issues that are commonly associated with flyback derived microinverters, such as i) the appearance of high voltage turn OFF spikes across the high frequency switch, ii) the requirement of lossy snubbers to control these voltage spikes, iii) the necessity for high turns ratio of the transformer and iv) poor efficiency due to the involvement of a higher number of components. The proposed topology involves only one high frequency switch. A resonance capacitor is employed which not only controls the turn OFF voltage spikes across this power switch but also ensures zero voltage turn ON (ZVS) for this switch. A coupled inductor based Ćuk configuration is incorporated in this topology wherein the energy trapped in the transformer leakage inductance is fed back to the grid, thereby improving the overall efficiency. Implementation of a dedicated boundary conduction control (BCM) strategy effectively limits the value of overall system ohmic losses and thereby ensures performance with enhanced efficiency. The inverter operating principle, the process for deriving the reference current expression, and the optimum design strategy for the inverter parameters are discussed in detail. A 220 W laboratory prototype is fabricated to validate the efficacy of the proposed scheme.

Bioinspired Stretchable MXene Deformation-Insensitive Hydrogel Temperature Sensors for Plant and Skin Electronics.

Temperature sensing is of high value in the wearable healthcare, robotics/prosthesis, and noncontact physiological monitoring. However, the common mechanic deformation, including pressing, bending, and stretching, usually causes undesirable feature size changes to the inner conductive network distribution of temperature sensors, which seriously influences the accuracy. Here, inspired by the transient receptor potential mechanism of biological thermoreceptors that could work precisely under various skin contortions, we propose an MXene/Clay/poly(N-isopropylacrylamide) (PNIPAM) (MCP) hydrogel with high stretchability, spike response, and deformation insensitivity. The dynamic spike response is triggered by the inner conductive network transformation from the 3-dimensional structure to the 2-dimensional surface after water being discharged at the threshold temperature. The water discharge is solely determined by the thermosensitivity of PNIPAM, which is free from mechanical deformation, so the MCP hydrogels can perform precise threshold temperature (32 °C) sensing under various deformation conditions, i.e., pressing and 15% stretching. As a proof of concept, we demonstrated the applications in plant electronics for the real-time surface temperature monitoring and skin electronics for communicating between human and machines. Our research opens venues for the accurate temperature-threshold sensation on the complicated surface and mechanical conditions.

Risk Factor Analysis of Death due to COVID-19 with Comorbid Condition in the Community of the Wetland Environment in Banjar District.

The prevalence of confirmed cases of COVID-19 is high and tends to continue to increase in Indonesia. Based on data, the Province of South Kalimantan, Indonesia in early mid-2021 experienced a high spike in cases, resulting in a large number of deaths, especially in Banjar Regency. Active COVID-19 cases in South Kalimantan in July 2021 were recorded at 5,279 (12.41%) out of 42,527 positive cases. Data compiled from the COVID-19 Task Force (Satgas) showed that Banjar Regency was the third highest area of the cumulative number of deaths, with as many as 47 people dying in one day. The results of many research on risk factors for COVID-19 cases vary widely. People with comorbidities are a very vulnerable group. This study aims to identify the relationship between comorbid conditions and death based on data from COVID-19 admission in the Wetland Environment community in Banjar Regency, South Kalimantan, Indonesia in the years 2020-2021. This is a retrospective analytical observational study which used purposive sampling. The data were collected from the case form report (CFR). The dependent variable in this study was inpatients at Ratu Zaleha Hospital who died and were diagnosed as positive for COVID-19, while the independent variables were age (productive/non-productive), tuberculosis, hypertension, diabetes mellitus, asthma, pneumonia, heart disease, COPD (lung disease), HIV/AIDS, chronic kidney disease (CKD), and stroke (CVA). Data were analyzed by univariate, bivariate, and multivariate analyses with logistic regression method to obtain adjusted OR. Out of 700 patients with confirmed COVID-19 infection, 273 (39%) had no comorbidity while 427 (61%) had at least one comorbid condition. There were 330 (47.1%) male patients and 370 (52.9%) female patients. There were 565 (80.7%) patients who belong in the productive age and 135 (19.35%) in the non-productive age. Results showed that age (p=0.002), asthma (p=0.026), chronic kidney disease (p=0.000), and heart disease (p=0.002) are significant risk factors of COVID-19 death in Banjar Regency. Based on our analysis of COVID-19-related deaths in Banjar Regency in Ratu Zaleha Hospital on the year 2020-2021, diabetes, pneumonia, kidney failure, and COPD were associated with increased mortality.

Design of Leaky Integrate and Fire Neuron for Spiking Neural Networks Using Trench Bipolar I-MOS

In this paper, using calibrated 2-D TCAD simulations we report a trench Bipolar I-MOS for the realization of a spiking neural network. We demonstrated that the proposed trench Bipolar I-MOS LIF neuron can emulate the biological neuronal nature and exhibits a low threshold voltage (-0.16 V), which is ∼ |400 mV| lower than the past reported LBIMOS LIF neuron. Moreover, the trench Bipolar I-MOS neuron consumes 0.35 pJ energy per spike, which is ∼ 100x lower in comparison to the PDSOI LIF neuron. Further, the proposed LIF neuron shows ∼ 10x reduction in energy per spike than the recently published Ge MOSFET and JLFET based LIF neurons. In addition, the proposed trench Bipolar I-MOS LIF neuron exhibits ∼ 6 orders high spiking frequency than the biological neuron. Also, the proposed device shows a ∼ 1.1x reduction in the breakdown voltage as compared to the conventional Bipolar I-MOS. This is due to the crowding of the electric field near the gate edges.

Agile Governance In Handling the Covid-19 Pandemic by The Kampar District Health Office in 2021

The concept of agile governance or called government that is agile, agile or fast has started to be discussed recently. Agile Governance increasingly has a strategic value in the midst of the condition of the Indonesian state which has been hit by the Covid-19 pandemic since 2020. The highest spike in Covid-19 cases in Kampar Regency occurred in August 2021 since the establishment of Covid-19 as a pandemic on March 31 2020. The purpose of this research is to find out how Agile Governance is implemented in efforts to deal with the Covid-19 pandemic carried out by the Health Service Kampar Regency. This study uses a qualitative research method with an explanatory approach. Researchers conducted data analysis based on the Agile Governance concept of Shah and Stephens’s theory. The research was conducted at the Kampar District Health Office in 2021. The results of this study indicate that the Health Office has implemented Agile Governance in an effort to deal with the Covid-19 pandemic in accordance with the applicable technical guidelines and standard operating procedures, but public distrust of Covid-19 has become obstacles for the Health Office in handling and providing services to the community in the Kampar Regency area.

Drop-weight impact responses and energy absorption of lightweight glass fiber reinforced polypropylene composite hierarchical cylindrical structures

A high spike force at the beginning of impact and the load fluctuations caused by unstable plateau deformation are disadvantages to avoid for impact resistance structures. Lightweight glass fiber-reinforced polypropylene composite hierarchical cylindrical structures (namely GFRP-CHCS, with a relative density of less than 0.1) have the potential to achieve low initial force and high crushing force efficiency under dynamic conditions. This work explores the drop-weight impact behaviors and energy absorption capacity of GFRP-CHCS. Deformation modes, failure conditions, and impact load history responses are discussed. Results showed that GFRP-CHCS has no initial load peak and achieves gentle response curves under the low-velocity impact when the load speed is less than 10 m/s. Among the experiments where the impact energy was beyond the range of static energy absorption, more than 94% of the impact energy was absorbed or dissipated when the impact energy ranged from 200 J to 300 J. After unloaded, GFRP-CHCS maintained good integrality and recovered a significant deformation which was over 93% initial structural height. With ideal isotropic material properties, numerical and theoretical predictions were conducted regarding the loading velocity effects on structural deformation mode and mean impact response force. This work utilized a thermoplastic composite consisting of GFRP face sheets and polypropylene core. The results have reference significance for the anti-impact design of thermoplastic composite hierarchical structures.

EARLY-LIFE PROTEIN TRANSLATION SPIKE DRIVES AGING VIA JUVENILE HORMONE/GERMLINE STEM CELL SIGNALING

Abstract Protein translation (PT) is high in early-adulthood across invertebrates, rodents, and humans but sharply declines thereafter. It has been implicitly assumed that elevated PT at young ages is beneficial to health and PT ends up dropping as a passive byproduct of aging. However, whether this holds true and how dynamic fluctuations in PT over time impact aging remain unknown. In Drosophila, we show that a transient PT spike in early-adulthood exerts long-lasting negative impacts on aging trajectories and proteostasis in later-life. Conversely, blocking the early-life PT spike robustly improves life-/health-span and prevents age-related protein aggregation. Further, greater early-life PT rise strongly predicts shorter future lifespan across fly strains and is observed in neurodegenerative disorders long before symptoms/pathologies appear. Proteomics-guided investigations revealed that during the early-adulthood PT rise, juvenile hormone triggers proteostatic dysfunction and drives aging via aggregation-prone large lipid transfer proteins. The early-life PT spike also transcriptionally represses stress responses essential for proteostasis maintenance and drives aging via germline stem cell signaling. Our findings suggest that PT is thereby suppressed after early-adulthood as an adaptive response to alleviate proteostatic burden, slow down aging, and optimize life-/health-span. We thus propose that the rise and fall in PT over time impact aging in the opposite direction from what was previously assumed. Our work provides a novel theoretical framework for understanding how lifetime PT dynamics regulate the onset of aging. Further, our study provides a foundation for future research, including whether high early-life PT spike is an early biological event driving neurodegeneration/age-related diseases.

High resolution radiocarbon spike confirms tree ring dating with low sample depth

Radiocarbon (14C) has been used to date carbon-rich objects in Earth science, archeology, and history since the 1940s. New methods, using spikes in 14C caused by solar proton events, can be used to annually date wood when crossdating is not possible, such as when sample size is low, samples are floating in time, or external disturbances lead to insecure dates. Here, we use a spike in radiocarbon during a solar energetic particle (SEP) event in 774/775 CE to confirm crossdating of a poorly-replicated King Billy pine (Athrotaxis selaginoides) chronology. Low sample depth between 1498 and 1523 CE (two trees) prevented confident dating of the early period of the chronology. Three core samples with strong correlation with the master chronology that likely included the 774/775 CE Miyake SEP event were identified for radiocarbon isotope analysis. We sectioned segments centered on the estimated 774/775 CE date and then isolated the holocellulose in each sample. Samples were sent to an accelerator mass spectrometry (AMS) for radiocarbon measurements. The AMS data confirmed the crossdating accuracy of the tree ring series and reinforces the applicability of this technique to anchor poorly dated tree ring series in time. In addition, we found sample processing with a microtome proved superior for holocellulose extractions and yielded more accurate 14C measurements. We recommend sampling with a microtome, processing at least three samples per year, and including sample masses greater than 100 ug C to confirm dating using radiocarbon spikes.

302. Using Severe Acute Respiratory Syndrome Coronavirus-2 Spike Protein Antibody Serology in addition to the ISARIC 4C Risk Score to Better Discriminate Adverse Clinical Outcomes in Hospitalized Patients with Coronavirus Disease 2019.

Abstract Background The Coronavirus disease 2019 (COVID-19) pandemic continues to threaten many countries globally. Large-scale vaccination exercises have helped to reduce transmission and severity of disease. We sought to modify an existing clinical score (the ISARIC-4C mortality score) to include serological status to better prognosticate hospitalized patients with COVID-19. Methods We examined the first 1781 consecutive hospitalized patients with polymerase chain reaction (PCR) confirmed COVID-19 in a tertiary academic centre. We divided the study population into those requiring intensive care and those who did not require throughout their inpatient stay. Baseline characteristics examined include medical comorbidities, vaccination status, SARS-CoV-2 serology spike protein, duration of fever and haemodynamics were compared. Adverse outcomes were defined as patients who required intensive care or mortality. Performance of the risk scores were measured by the area under receiver operating characteristic curves (AUC) in predicting adverse outcomes. Results The 55 patients requiring intensive care during their inpatient stay tended to have persistent fever beyond 72 hours and had lower titres of spike protein antibodies. (58.9 (±105.3) U/mL vs 144.2 (±116.2) U/mL, p = 0.007). A high spike protein antibody titre &amp;gt;75 U/mL was independently protective for adverse outcomes (adjusted OR 0.15, 95% CI 0.04-0.53), even after adjusting for the ISARIC-4C score and the presence of persistent fever. Adding the serological status and presence of persistent fever to the ISARIC-4C score improved its performance in predicting adverse outcomes (AUC 0.84, 95% CI 0.78-0.89). Conclusion Addition of the SARS-CoV-2 serology spike protein titre and prolonged fever to the ISARIC-4C mortality score helps to better prognosticate adverse clinical outcomes in hospitalized patients with COVID-19. Disclosures All Authors: No reported disclosures.

GAMBARAN KEJADIAN COVID-19 DI WILAYAH KERJA PUSKESMAS UMBULHARJO I (PERIODE BULAN MEI – AGUSTUS 2021)

COVID-19 cases since the beginning of 2020 have experienced a fluctuating increase. This incident is caused by a virus that can attack everyone with a high level of transmission. Characteristics of events in each region may be different. Therefore, knowing the distribution of epidemiology in an area is important to study. The purpose of this study was to determine the epidemiological description based on people, place, and time in the working area of the Umbulharjo I Health Center. This study used an analytical descriptive method with secondary data sources derived from the results of an epidemiological investigation conducted in May – August 2021. The results of this study indicate that the majority of COVID-19 cases in the working area of the Umbulharjo I Health Center are women, aged 26-35 years, with the highest area in Kelurahan 3 which has a higher population density than other areas, and the highest spike in cases occurred in The month of July with the most daily cases occurred on 28-29 June 2021.